Director of Engineering - AI

🏢 Summary: Senior platform product role owning the AI infrastructure powering multi-agent banking assistants across voice and digital channels. Responsible for defining technical direction, model lifecycle, orchestration, performance, safety, and platform contracts to scale to millions of users. Acts as a senior IC setting standards for AI-native, enterprise-grade, multi-tenant systems. 🗂️ Requirements: 8+ years product management experience, 3+ years at Staff/Principal level on platform, AI/ML, or infrastructure products, Experience owning multi-component platform used by multiple product teams, Ability to read code, review architecture, and debug production issues, Experience with LLM orchestration, evaluation, and fine-tuning pipelines, Experience defining and governing APIs, versioning, and platform contracts, Experience in enterprise SaaS with multi-tenant and compliance requirements, Knowledge of inference optimization and latency management for real-time systems 📃 Skills: LLM, RAG, RLHF, RLAIF, APIs, ASR, TTS, Python, Quantization, Encryption, SOC2, GDPR, Cursor, Copilot 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.Company: interface.ai Location: Palo Alto, CA (In-Office) Reports to: VP of Product Compensation: $250,000 - $320,000 base salary + bonus + equity (depending on location & experience) About interface.ai Banking hasn't kept up with how people actually live their financial lives. At interface.ai, we're building AI-native products that transform how millions of Americans interact with their financial institutions, making every interaction intelligent, personal, and proactive.Our platform powers AI agents that handle real banking tasks end-to-end: moving money, resolving issues, converting loans, and surfacing financial insights across voice, chat, and digital channels. We're not building another chatbot. We're building the AI infrastructure that will become the primary way people bank, unlocking a massive market opportunity by displacing the legacy systems that financial institutions have been stuck with for decades. With two-thirds of Americans living paycheck to paycheck, only 17% financially literate, and 50% holding less than $500 in savings, the urgency is real. We're putting financial well-being on autopilot. We power AI agents for 100+ financial institutions, serving millions of banking members across the U.S., and are backed by leading investors including Avataar Venture Partners and Blume Ventures. Our platform enables banks and credit unions to automate high-volume customer interactions across voice and digital channels while improving resolution rates, reducing operational costs, and increasing customer engagement. Key credibility anchors: Series B AI company building agentic AI infrastructure for financial institutions Trusted by 100+ banks and credit unions across North America Serving millions of end users through conversational AI across voice, chat, and mobile channels The Opportunity You will own the AI platform that every product at the company depends on. This is not a support function: the platform is the competitive moat. Your decisions directly determine the ceiling of what every other product team can build. You'll inherit a multi component platform, assess what exists, and define what comes next: what to consolidate, what to invest in, what to sunset. As the senior IC in a pillar of 3-4PMs, you'll set technical direction, mentor, and raise the quality bar, while partnering with engineering leadership to scale the system to millions of end users at startup speed. What You'll Own Agent runtime & orchestration: multi-agent orchestration, memory/context management, tool routing, goal planning, and policy-aligned behavior Platform contracts: APIs, versioning, deprecation, and migration strategy: you define the boundaries and the lifecycle for all consuming teams Model lifecycle: selection, evaluation, benchmarking, fine-tuning enablement, and prompt optimization. You define when to prompt-tune vs fine-tune vs switch models. Inference performance & reliability: latency budgets, caching, batching, quantization, multi-region deployments, fallbacks, and safe rollout patterns (canaries, feature flags, rollback) Safety & compliance: PII detection/masking, prompt/response safety policies, tenant isolation, SOC2/GDPR readiness, audit logs, and encryption: compliance is a product requirement, not an afterthought Evaluation & quality: offline golden sets, regression testing, hallucination measurement, task success metrics, and production-to-improvement feedback loops Voice & multimodal: ASR/TTS integration patterns, WER, interruption handling, turn-taking, and latency budgets for real-time conversational intelligence Pillar leadership: You set technical direction, mentor, raise the bar, and have input on hiring. You prioritize competing demands from multiple product pillars, define the platform investment thesis, and protect the platform from becoming a feature factory. Who You Are You think in systems, not features. You read a platform outage postmortem and immediately see the product decision that caused it. You've built API contracts that entire product orgs depend on, and you've made the hard call to break one when the platform needed to evolve. You understand the full AI stack: from model training through inference optimization to production monitoring. You can spec a fine-tuning pipeline, set latency budgets for real-time voice, and debate quantization trade-offs with a staff engineer, all in the same week. You build your own tools. You use AI to prototype, analyze, and accelerate your work — building agents, writing scripts, creating automated workflows, whatever gets the job done fastest. Not because someone told you to, but because you can't imagine working any other way. What You Bring 8+ years in product management, with 3+ years at Staff/Principal level on platform, AI/ML, or infrastructure products Owned a multi-component platform serving multiple product teams, not just a single product Deep technical fluency: can read code, review architecture, and debug production issues alongside engineers Experience with AI/ML platforms: LLM orchestration, model evaluation, fine-tuning, RAG, agentic frameworks, or similar Experience governing platform contracts and managing how internal teams consume capabilities Built in enterprise SaaS environments with multi-tenant, compliance, and governance requirements AI-native workflow: You build with AI daily — creating agents, automating analyses, prototyping with code, building custom workflows. The specific tools don't matter (Cursor, Copilot, Claude, Replit, custom scripts — all count); what matters is that you've moved beyond prompting into building. Bonus Points Financial services or regulated industry experience Voice/ASR/TTS systems and real-time latency-sensitive products LLM evaluation frameworks, multi-agent orchestration, or RLHF/RLAIF Knowledge graph or RAG-based retrieval systems Built a platform team from scratch Our Values Act Like You're the Founder: Own the outcome from start to finish No Fear. Speak Your Mind: Candor moves us forward Pursuit of Excellence: Raise the bar, every time AI-First Mindset: Think automation, intelligence, and scale-first in every solution Don't Assume. Seek to Understand: Start with questions, not conclusions How We Work Every PM builds with AI daily. Our standard toolkit is Cursor, MCP integrations, and custom AI agents — and we onboard every new hire on these tools in their first week. We hold a high quality bar and move at startup speed. Flat organization. No empire-building. What We Offer 100% company-paid medical, dental, and vision coverage 401(k) with company match and financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness, and family benefits Competitive equity with meaningful upside At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Senior platform product leader role owning the AI infrastructure powering a universal banking assistant used by millions. Responsible for defining and scaling multi-agent orchestration, model lifecycle, platform APIs, inference performance, and compliance across voice and digital channels. Sets technical direction for the AI platform, enabling product teams to build on a secure, reliable, and high-performance foundation. 🗂️ Requirements: 8+ years product management experience, 3+ years at Staff/Principal level on platform, AI/ML, or infrastructure products, Experience owning multi-component platform serving multiple teams, Ability to read code and review system architecture, Experience with LLM orchestration and model evaluation, Experience defining and governing platform APIs and contracts, Experience in enterprise SaaS with multi-tenant architecture, Knowledge of inference optimization and latency management, Experience with compliance and security in regulated environments 📃 Skills: LLM, RAG, RLHF, APIs, Microservices, Python, ASR, TTS, Quantization, Fine-tuning, Orchestration, Multi-agent, Benchmarking, Encryption, SOC2, GDPR, Cursor, Copilot 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.Company: interface.ai Location: Palo Alto, CA (In-Office) Reports to: VP of Product Compensation: $250,000 - $320,000 base salary + bonus + equity (depending on location & experience) About interface.ai Banking hasn't kept up with how people actually live their financial lives. At interface.ai, we're building AI-native products that transform how millions of Americans interact with their financial institutions, making every interaction intelligent, personal, and proactive.Our platform powers AI agents that handle real banking tasks end-to-end: moving money, resolving issues, converting loans, and surfacing financial insights across voice, chat, and digital channels. We're not building another chatbot. We're building the AI infrastructure that will become the primary way people bank, unlocking a massive market opportunity by displacing the legacy systems that financial institutions have been stuck with for decades. With two-thirds of Americans living paycheck to paycheck, only 17% financially literate, and 50% holding less than $500 in savings, the urgency is real. We're putting financial well-being on autopilot. We power AI agents for 100+ financial institutions, serving millions of banking members across the U.S., and are backed by leading investors including Avataar Venture Partners and Blume Ventures. Our platform enables banks and credit unions to automate high-volume customer interactions across voice and digital channels while improving resolution rates, reducing operational costs, and increasing customer engagement. Key credibility anchors: Series B AI company building agentic AI infrastructure for financial institutions Trusted by 100+ banks and credit unions across North America Serving millions of end users through conversational AI across voice, chat, and mobile channels The Opportunity You will own the AI platform that every product at the company depends on. This is not a support function: the platform is the competitive moat. Your decisions directly determine the ceiling of what every other product team can build. You'll inherit a multi component platform, assess what exists, and define what comes next: what to consolidate, what to invest in, what to sunset. As the senior IC in a pillar of 3-4PMs, you'll set technical direction, mentor, and raise the quality bar, while partnering with engineering leadership to scale the system to millions of end users at startup speed. What You'll Own Agent runtime & orchestration: multi-agent orchestration, memory/context management, tool routing, goal planning, and policy-aligned behavior Platform contracts: APIs, versioning, deprecation, and migration strategy: you define the boundaries and the lifecycle for all consuming teams Model lifecycle: selection, evaluation, benchmarking, fine-tuning enablement, and prompt optimization. You define when to prompt-tune vs fine-tune vs switch models. Inference performance & reliability: latency budgets, caching, batching, quantization, multi-region deployments, fallbacks, and safe rollout patterns (canaries, feature flags, rollback) Safety & compliance: PII detection/masking, prompt/response safety policies, tenant isolation, SOC2/GDPR readiness, audit logs, and encryption: compliance is a product requirement, not an afterthought Evaluation & quality: offline golden sets, regression testing, hallucination measurement, task success metrics, and production-to-improvement feedback loops Voice & multimodal: ASR/TTS integration patterns, WER, interruption handling, turn-taking, and latency budgets for real-time conversational intelligence Pillar leadership: You set technical direction, mentor, raise the bar, and have input on hiring. You prioritize competing demands from multiple product pillars, define the platform investment thesis, and protect the platform from becoming a feature factory. Who You Are You think in systems, not features. You read a platform outage postmortem and immediately see the product decision that caused it. You've built API contracts that entire product orgs depend on, and you've made the hard call to break one when the platform needed to evolve. You understand the full AI stack: from model training through inference optimization to production monitoring. You can spec a fine-tuning pipeline, set latency budgets for real-time voice, and debate quantization trade-offs with a staff engineer, all in the same week. You build your own tools. You use AI to prototype, analyze, and accelerate your work — building agents, writing scripts, creating automated workflows, whatever gets the job done fastest. Not because someone told you to, but because you can't imagine working any other way. What You Bring 8+ years in product management, with 3+ years at Staff/Principal level on platform, AI/ML, or infrastructure products Owned a multi-component platform serving multiple product teams, not just a single product Deep technical fluency: can read code, review architecture, and debug production issues alongside engineers Experience with AI/ML platforms: LLM orchestration, model evaluation, fine-tuning, RAG, agentic frameworks, or similar Experience governing platform contracts and managing how internal teams consume capabilities Built in enterprise SaaS environments with multi-tenant, compliance, and governance requirements AI-native workflow: You build with AI daily — creating agents, automating analyses, prototyping with code, building custom workflows. The specific tools don't matter (Cursor, Copilot, Claude, Replit, custom scripts — all count); what matters is that you've moved beyond prompting into building. Bonus Points Financial services or regulated industry experience Voice/ASR/TTS systems and real-time latency-sensitive products LLM evaluation frameworks, multi-agent orchestration, or RLHF/RLAIF Knowledge graph or RAG-based retrieval systems Built a platform team from scratch Our Values Act Like You're the Founder: Own the outcome from start to finish No Fear. Speak Your Mind: Candor moves us forward Pursuit of Excellence: Raise the bar, every time AI-First Mindset: Think automation, intelligence, and scale-first in every solution Don't Assume. Seek to Understand: Start with questions, not conclusions How We Work Every PM builds with AI daily. Our standard toolkit is Cursor, MCP integrations, and custom AI agents — and we onboard every new hire on these tools in their first week. We hold a high quality bar and move at startup speed. Flat organization. No empire-building. What We Offer 100% company-paid medical, dental, and vision coverage 401(k) with company match and financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness, and family benefits Competitive equity with meaningful upside At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Executive technical leadership role to scale and evolve a global AI-driven brand compliance platform built on cloud-native architecture. The position focuses on defining technical vision, overseeing scalable and resilient systems on GCP, and integrating AI/ML into production-grade products. The mission is to transform the engineering organization into a high-performance team while maintaining startup agility. 🗂️ Requirements: Proven experience as CTO, VP Engineering, or Head of Tech in startup environment, Expert knowledge of Java, Python, and React, Strong experience with cloud-native architectures on GCP, Experience building data-intensive platforms, Experience integrating AI/ML into production systems, Experience designing scalable microservices architectures, Experience with event-driven systems, Ability to define and execute technical strategy, Experience leading and scaling cross-functional engineering teams 📃 Skills: Java, Python, React, GCP, Microservices, GraphQL, AI, ML, NLP, DevOps, QA, Cloud, Architecture, Event-driven 🏢 Description: What’s at stake? We’re changing the rules of the game in global brand compliance. Our product is in an extremely dynamic phase of development, and the largest e-commerce platforms on the market are already taking a direct interest in our innovative approach. What gives us a massive advantage is access to unique datasets—powerful fuel for building advanced AI-based solutions. We’re looking for a leader who will step up and take our product to the very top! Your mission and challenge : We need a technological visionary who will take the helm and transform our product and engineering organization into a high-performance machine. You must know how to scale processes and architecture without losing the agility and startup spirit that drives us. Our Tech Stack We build on a robust and modern foundation: Backend: Java (modern frameworks, microservices architecture). Frontend: React (building intuitive, data-rich management dashboards). AI/ML Module: Python (dedicated models for natural language processing of regulations and automated decision-making). Infrastructure: Google Cloud Platform (GCP). Engineering Philosophy: High focus on "Compliance by Design," high availability, and seamless integration with global regulatory data sources. Key Responsibilities Technical Strategy: Define the long-term technical vision and roadmap, ensuring the platform remains "right by design" and scalable for global markets. Architecture Oversight: Oversee the evolution of the GCP and Event-driven infrastructure, ensuring high resilience and security. Team Leadership: Scale and mentor a cross-functional engineering team (Software, Data, AI, DevOps, QA), fostering a culture of high velocity and low ego. Product-Tech Alignment: Collaborate with stakeholders to translate complex burdens into elegant, automated digital products. Innovation: Drive the integration of AI/ML and GraphQL layers. Requirements Leadership: Proven experience in executive technical leadership (CTO, VP Engineering, or Head of Tech) in a fast-paced startup environment. Deep Technical Roots: Expert knowledge of modern stacks (java, python, react) and cloud-native architectures (GCP). Data & AI Vision: Experience building data-heavy platforms and integrating AI/ML into production workflows. Business Acumen: Ability to align technical decisions with commercial goals and regulatory requirements. Mindset: A pragmatic leader who stays "close to the code," values ownership, and thrives on solving high-impact problems.

🏢 Summary: Senior Product Manager role owning a multi-product AI banking suite (chat, voice, and digital) used by financial institutions, driving product direction, optimization, and growth across a shared AI platform. Responsible for scaling AI-powered member experiences, improving automation quality, and aligning multi-channel products into a seamless system. Acts as senior individual contributor leading portfolio strategy and leveraging AI-native workflows to manage and enhance product performance. 🗂️ Requirements: 8+ years product management experience, 3+ years managing multiple products simultaneously, Experience shipping AI-powered products where AI is core, Experience optimizing and growing B2B SaaS products, Strong UX expertise for member-facing products, Experience presenting to US financial institution executives, Experience leading product direction as senior IC, Hands-on use of AI tools for analytics, automation, and workflows, Experience with multi-channel products (chat, voice, digital), Experience building or working with custom AI agents or AI workflows 📃 Skills: AI, SaaS, UX, VoiceAI, ConversationalAI, Automation, Analytics, Dashboards, Agents, MCP, Cursor, Copilot, Claude, Replit, Scripts, APIs 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role: You're taking ownership of the product portfolio that drives the majority of interface.ai's current revenue: a multi-product AI suite spanning chat, voice, and digital channels, deployed across a large and growing base of financial institutions. This is an operator's challenge at a critical growth moment. Assess health across products, prioritize ruthlessly, and drive improvements that compound across the entire suite. The products share a common AI platform, and your job is to make them work together seamlessly while pushing each product's metrics higher. You'll be the senior IC and product anchor for the member-facing product pillar, setting product direction, mentoring peer PMs, breaking ties, and ensuring the existing products continue to deliver while the company invests in the future. Key Responsibilities AI-powered digital banking: The chat-based member experience, covering account management, transactions, service resolution, and more AI-powered voice banking: The same core capabilities delivered through phone-based conversational AI, with a focus on automation quality and member experience AI-powered conversion: End-to-end workflows that guide members through applications and complex financial actions across chat and voice, turning intent into completionProactive intelligence: How the platform surfaces the right information, reminders, insights, and opportunities to members at the right time across all channels Pillar leadership: Set product direction for the member-facing pillar. Mentor PMs, have input on hiring, and raise the quality bar Required Qualifications 8+ years in product management, with 3+ years managing multiple products simultaneously (not sequentially) Experience shipping "AI-powered products with a high quality bar" where AI was core to the experience, not a bolt-on feature Strong UX sensibility member-facing products demand high craft quality Track record optimizing and growing existing B2B SaaS products, not just 0-to-1 building Customer-facing: comfortable presenting to and working with US-based financial institution executives Experience as a senior IC leading a product line setting direction for and mentoring 2-3+ PMs through influence (not people management) AI-native workflow: You build with AI daily — analyzing user data, drafting specs, building dashboards, automating workflows. The specific tools don't matter (Cursor, Copilot, Claude, Replit, custom scripts — all count); what matters is that you've moved beyond prompting into building. This is how you manage the breadth of a multi-product portfolio without drowning in it. Preferred Skills Voice AI or conversational AI product experience Financial services or financial institution industry knowledge Built AI-powered products at scale (millions of end users) Experience with multi-channel product experiences (voice + chat + digital) Built custom AI agents, MCP integrations, or automated AI workflows for product management tasks Who you are? You're the operator who walks into a multi-product portfolio and within weeks knows exactly which product is healthy, which is underperforming, and which metric to move first. You don't just manage products, you manage a *system* of products that share infrastructure, serve overlapping users, and compound in value when they work together. You've been the person that enterprise customers trust. You can walk into a room of financial institution executives, understand their pain in the first ten minutes, and translate it into a product improvement by the end of the week. You balance customer empathy with business discipline: you won't build something just because a customer asks, but you'll never dismiss a pain point without investigation. You build your own tools and workflows. You use AI to track portfolio health, analyze usage patterns at scale, prototype product improvements, and automate the parts of product management that don't require human judgment — building agents, creating automated workflows, writing scripts, whatever makes the work faster. You manage a multi-product portfolio at a pace that would be impossible without AI, and that's the point. Our Values Act Like You're the Founder: Own the outcome from start to finish No Fear. Speak Your Mind: Candor moves us forward Pursuit of Excellence: Raise the bar, every time AI-First Mindset: Think automation, intelligence, and scale-first in every solution Don't Assume. Seek to Understand: Start with questions, not conclusions How We Work? Every PM builds with AI daily. Our standard toolkit is Cursor, MCP integrations, and custom AI agents — and we onboard every new hire on these tools in their first week. We hold a high quality bar and move at startup speed. Flat organization. No empire-building. Compensation Base Salary is expected to be between $250,000 - $320,000, plus 10%bonus and stock options. Exact compensation may vary based on skills and location. We're an in-office company in Bay area, driven by a shared commitment to excellence and velocity. This role is based in our Palo Alto office and is expected to work on-site with the team. Benefits 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Senior full-stack product engineering role focused on building and owning AI-native web product experiences end-to-end across frontend and backend. The position involves shipping production-ready features, designing APIs and data flows, improving usability and reliability, and using AI tools daily in a fast-growing engineering environment. The role is office-based in Warsaw and offers strong ownership, modern tooling, and participation in AI-powered product development. 🗂️ Requirements: Senior-level experience shipping production web products, Strong React skills, Strong TypeScript skills, Backend API design and implementation experience, Experience building backend logic and data flows, Ability to work across frontend and backend, Security-conscious engineering approach, Experience collaborating with product and design teams, Daily use of AI tools in engineering workflows, Clear technical communication 📃 Skills: React, TypeScript, Python, Node.js, APIs, AI, Codex, Claude, GitHub, Copilot 🏢 Description: About Shelf The enterprise is going agentic and we are creating a unique operating system for an automated future. Most AI agents break the moment they hit real business complexity. That’s why we built a platform that models a company's policies, workflows, and operational logic into an AI Data Model. Shelf enables AI Agents to reliably reason and deliver precise and reliable outcomes at scale. We already have what most AI startups are still trying to earn: Enterprise customers such as Glovo, Nespresso, and HelloFresh, real production data, and tens of thousands of users. Customers trust us with operational knowledge: Our platform is highly reliable and secure with SOC2, HIPAA-ready security practices, and mature integrations in place. Job Description This role is for a senior full-stack product engineer who can design and own business-critical product experiences end-to-end. We want someone who is strong technically, has sharp product judgment, communicates clearly, and has the taste to make user experiences and systems simpler, safer, and easier to evolve over time. Expect real ownership from problem discovery through frontend, backend, release, and production quality. The team is small enough for engineers to make real decisions. Career growth comes from ownership. Titles matter less than the scope you can carry. The people who grow fastest take responsibility for larger product areas, drive customer outcomes, and strive to develop better engineering practices. You solve ambiguous product problems by understanding the customer need, shaping the right technical and UX approach, then shipping, iterating, and keeping it healthy in production. We build AI-native. Engineers use Codex, Claude Code, and agents they build themselves. We invest in harness engineering through skills, CLIs, logs, traces, and orchestration. This is a role for someone in a high-growth chapter of their career, who wants to do the best work of their life, learn fast, and win as part of a team going all-in on a hard mission. Location – Warsaw, work from the office. What You Will Own Build and ship user-facing product features across frontend and backend boundaries Turn rough product goals into practical solutions with good scope, sensible trade-offs, and strong execution Work comfortably in UI, application logic, APIs, and data flows rather than stopping at team boundaries Partner closely with product and design while still being able to move when the spec is incomplete Improve usability, clarity, performance, and reliability, not just feature completeness Instrument what you ship so we can learn from production behavior and iterate quickly Use AI tools daily to move faster and help improve internal workflows, tooling, and engineering leverage Keep the bar high on code quality, testing, and ownership after launch What Strong Performance Looks Like You can take a vague product problem and turn it into a shipped, well-reasoned solution Your features feel coherent end-to-end because you care about both implementation and product quality You do not treat frontend and backend as separate worlds; you use both to solve the actual problem You bring momentum. Work moves because you are on it What We Are Looking For Strong senior-level experience shipping production web products Strong frontend ability with React and TypeScript or an equivalent modern web stack Real backend ability. You do not need to be backend-only, but you can design and ship APIs, backend logic, and data flows when the product needs it Strong product sense. You notice awkward flows, weak defaults, and unnecessary complexity, and you improve them Good judgment about scope, iteration, and technical trade-offs A security-conscious approach to engineering: you handle sensitive data carefully and think about the security implications of what you ship Clear communication and comfort working across engineering, product, and design AI-native working style. You already use AI tools as part of daily implementation and problem solving, and you are excited to improve how engineering work gets done Strong Plus Experience with AI-powered product experiences such as chat, search, recommendations, workflows, or agent-like systems Experience with Python, Node.js, or both on the backend Experience owning product areas with limited oversight Strong feel for performance, accessibility, and production quality in complex web applications How We Evaluate Fit We care more about end-to-end ownership, product sense, and the ability to ship meaningful work than a perfect match to every framework on paper. If you are the kind of engineer who can make a product better from multiple angles, we want to talk. What Shelf Offers B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. A strong AI-native engineering environment with modern tools and room to experiment, including Claude Code, OpenAI Codex, and GitHub Copilot. Why Shelf Becoming one of the defining companies of the AI age is a hard plan, and our leadership team has the rare mix of deep AI, knowledge-management, and enterprise SaaS experience to actually execute it We have raised over $60 million in funding; our investors include Tiger Global, Insight Partners, Base10, and others Recognized by Gartner as a Cool Vendor, with high-velocity growth powered by the most innovative product in our category We love our customers and our customers love us. Ask a Shelf customer why, and they'll tell you it's our innovative capabilities and rock-solid reliability, that they enjoy working with our people, and most of all, the improvements they see in their business KPIs We're building fast across three hubs: our New York HQ and our Product and Engineering centers in Warsaw and Lviv

🏢 Summary: Senior full-stack product engineering role focused on building and owning AI-native web product experiences across frontend and backend systems. The position involves end-to-end ownership of product features, collaboration with product and design teams, and improving performance, usability, and reliability in production. The role offers work with modern AI engineering tools and a high-growth environment in Warsaw. 🗂️ Requirements: Senior-level experience shipping production web products, Strong frontend skills with React, Strong frontend skills with TypeScript, Ability to design and ship APIs, Experience with backend logic and data flows, Strong product sense, Understanding of technical trade-offs and scope management, Security-conscious engineering approach, Clear communication across engineering, product, and design, Daily use of AI tools in engineering workflows, Ability to work from the Warsaw office 📃 Skills: React, TypeScript, Python, Node.js, APIs, AI, Codex, Claude, GitHub, Copilot 🏢 Description: About Shelf The enterprise is going agentic and we are creating a unique operating system for an automated future. Most AI agents break the moment they hit real business complexity. That’s why we built a platform that models a company's policies, workflows, and operational logic into an AI Data Model. Shelf enables AI Agents to reliably reason and deliver precise and reliable outcomes at scale. We already have what most AI startups are still trying to earn: Enterprise customers such as Glovo, Nespresso, and HelloFresh, real production data, and tens of thousands of users. Customers trust us with operational knowledge: Our platform is highly reliable and secure with SOC2, HIPAA-ready security practices, and mature integrations in place. Job Description This role is for a senior full-stack product engineer who can design and own business-critical product experiences end-to-end. We want someone who is strong technically, has sharp product judgment, communicates clearly, and has the taste to make user experiences and systems simpler, safer, and easier to evolve over time. Expect real ownership from problem discovery through frontend, backend, release, and production quality. The team is small enough for engineers to make real decisions. Career growth comes from ownership. Titles matter less than the scope you can carry. The people who grow fastest take responsibility for larger product areas, drive customer outcomes, and strive to develop better engineering practices. You solve ambiguous product problems by understanding the customer need, shaping the right technical and UX approach, then shipping, iterating, and keeping it healthy in production. We build AI-native. Engineers use Codex, Claude Code, and agents they build themselves. We invest in harness engineering through skills, CLIs, logs, traces, and orchestration. This is a role for someone in a high-growth chapter of their career, who wants to do the best work of their life, learn fast, and win as part of a team going all-in on a hard mission. Location – Warsaw, work from the office. What You Will Own Build and ship user-facing product features across frontend and backend boundaries Turn rough product goals into practical solutions with good scope, sensible trade-offs, and strong execution Work comfortably in UI, application logic, APIs, and data flows rather than stopping at team boundaries Partner closely with product and design while still being able to move when the spec is incomplete Improve usability, clarity, performance, and reliability, not just feature completeness Instrument what you ship so we can learn from production behavior and iterate quickly Use AI tools daily to move faster and help improve internal workflows, tooling, and engineering leverage Keep the bar high on code quality, testing, and ownership after launch What Strong Performance Looks Like You can take a vague product problem and turn it into a shipped, well-reasoned solution Your features feel coherent end-to-end because you care about both implementation and product quality You do not treat frontend and backend as separate worlds; you use both to solve the actual problem You bring momentum. Work moves because you are on it What We Are Looking For Strong senior-level experience shipping production web products Strong frontend ability with React and TypeScript or an equivalent modern web stack Real backend ability. You do not need to be backend-only, but you can design and ship APIs, backend logic, and data flows when the product needs it Strong product sense. You notice awkward flows, weak defaults, and unnecessary complexity, and you improve them Good judgment about scope, iteration, and technical trade-offs A security-conscious approach to engineering: you handle sensitive data carefully and think about the security implications of what you ship Clear communication and comfort working across engineering, product, and design AI-native working style. You already use AI tools as part of daily implementation and problem solving, and you are excited to improve how engineering work gets done Strong Plus Experience with AI-powered product experiences such as chat, search, recommendations, workflows, or agent-like systems Experience with Python, Node.js, or both on the backend Experience owning product areas with limited oversight Strong feel for performance, accessibility, and production quality in complex web applications How We Evaluate Fit We care more about end-to-end ownership, product sense, and the ability to ship meaningful work than a perfect match to every framework on paper. If you are the kind of engineer who can make a product better from multiple angles, we want to talk. What Shelf Offers B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. A strong AI-native engineering environment with modern tools and room to experiment, including Claude Code, OpenAI Codex, and GitHub Copilot. Why Shelf Becoming one of the defining companies of the AI age is a hard plan, and our leadership team has the rare mix of deep AI, knowledge-management, and enterprise SaaS experience to actually execute it We have raised over $60 million in funding; our investors include Tiger Global, Insight Partners, Base10, and others Recognized by Gartner as a Cool Vendor, with high-velocity growth powered by the most innovative product in our category We love our customers and our customers love us. Ask a Shelf customer why, and they'll tell you it's our innovative capabilities and rock-solid reliability, that they enjoy working with our people, and most of all, the improvements they see in their business KPIs We're building fast across three hubs: our New York HQ and our Product and Engineering centers in Warsaw and Lviv

🏢 Summary: Senior backend engineering role focused on designing and owning production-grade backend systems for AI-native enterprise platforms. The position involves building scalable services, APIs, and distributed systems while improving reliability, observability, and engineering workflows with AI tooling. The role offers high ownership, collaboration across teams, and work on AI agents and enterprise-grade infrastructure. 🗂️ Requirements: Senior-level backend engineering experience, Strong Python skills, Experience designing production backend systems, Knowledge of distributed systems, Experience with AWS, GCP, or Azure, Database schema design and performance tuning, Security-conscious engineering approach, Ability to own systems from design to production, Clear written and verbal communication, Experience using AI tools in engineering workflows, Work from Warsaw office 📃 Skills: Python, AWS, GCP, Azure, TypeScript, APIs, AI, LLM, Codex, Claude, Copilot, GitHub, SQL, Concurrency, Orchestration 🏢 Description: About Shelf The enterprise is going agentic and we are creating a unique operating system for an automated future. Most AI agents break the moment they hit real business complexity. That’s why we built a platform that models a company's policies, workflows, and operational logic into an AI Data Model. Shelf enables AI Agents to reliably reason and deliver precise and reliable outcomes at scale. We already have what most AI startups are still trying to earn: Enterprise customers such as Glovo, Nespresso, and HelloFresh, real production data, and tens of thousands of users. Customers trust us with operational knowledge: Our platform is highly reliable and secure with SOC2, HIPAA-ready security practices, and mature integrations in place. Job Description: This role is for a senior backend engineer who can design and own business-critical systems. We want someone who is strong technically, communicates clearly, and has the judgment to make systems simpler, safer, and easier to evolve over time. Expect real ownership from system design through production. The team is small enough for engineers to make real decisions. Career growth comes from ownership. Titles matter less than the scope you can carry. The people who grow fastest take responsibility for larger systems, drive customer outcomes, and strive to develop better engineering practices. You solve ambiguous problems by shaping the right architectural approach, then ship, iterate, and keep it healthy in production. We build AI-native. Engineers use Codex, Claude Code, and agents they build themselves. We invest in harness engineering through skills, CLIs, logs, traces, and orchestration. This is a role for someone in a high-growth chapter of their career, who wants to do the best work of their life, learn fast, and win as part of a team going all-in on a hard mission. Location – Warsaw, work from the office. What You Will Own Design and ship backend services, APIs, data flows, and background processing for production systems Turn vague requirements into concrete technical plans, trade-offs, and execution Own services after launch: reliability, observability, performance, and incident follow-through Instrument what you ship and use production signal to iterate, not just to keep the lights on Make sound decisions around system boundaries, data models, interfaces, and scaling paths Work closely with product, frontend, and platform engineers to deliver end-to-end outcomes Improve engineering leverage with AI tooling, automation, and internal workflows rather than using AI as a gimmick Raise the quality bar through code review, design review, and pragmatic technical leadership What Strong Performance Looks Like You reliably move important backend work forward without waiting to be tightly managed. Your systems are easier to operate and easier to change because of your design decisions. You make smart trade-offs to unblock shipping - and you stand by those decisions. You keep raising the bar on engineering excellence for yourself and everyone else. What We Are Looking For Strong senior-level backend engineering experience in production systems Strong Python skills and the ability to design clean, maintainable backend code Good distributed systems judgment: concurrency, failure handling, data consistency, async work, and service boundaries Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure Comfort with database schema design and performance tuning for real-time and high throughput scenarios A security-conscious approach to engineering: you build for enterprise-grade requirements, handle sensitive data carefully, and think about the security implications of the systems and AI workflows you ship Ability to go from problem statement to design to production rollout with real ownership Clear written and verbal communication. You can explain systems, trade-offs, and incidents without hiding behind jargon AI-native working style. You already use AI tools in your daily engineering workflow, and you're excited to improve how the team builds, not just your own output: better tooling, workflows, and engineering leverage Strong Plus Experience building agentic systems: AI agents, tool-calling, orchestration, retrieval, or LLM-backed infrastructure in production Working knowledge of TypeScript or the ability to contribute across the stack when needed Experience shaping technical direction for other engineers, even without formal management responsibility How We Evaluate Fit We care more about ownership, systems judgment, and learning velocity than a perfect keyword match to our stack. If you are the kind of engineer who can take a messy problem and turn it into a strong production system, we want to talk. What Shelf Offers: B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. A strong AI-native engineering environment with modern tools and room to experiment, including Claude Code, OpenAI Codex, and GitHub Copilot. Why Shelf: Becoming one of the defining companies of the AI age is a hard plan, and our leadership team has the rare mix of deep AI, knowledge-management, and enterprise SaaS experience to actually execute it We have raised over $60 million in funding; our investors include Tiger Global, Insight Partners, Base10, and others Recognized by Gartner as a Cool Vendor, with high-velocity growth powered by the most innovative product in our category We love our customers and our customers love us. Ask a Shelf customer why, and they'll tell you it's our innovative capabilities and rock-solid reliability, that they enjoy working with our people, and most of all, the improvements they see in their business KPIs We're building fast across three hubs: our New York HQ and our Product and Engineering centers in Warsaw and Lviv

🏢 Summary: Senior Backend Engineer role focused on designing and owning production-grade backend systems for AI-native enterprise platforms. The position involves building scalable APIs, data flows, and distributed systems with strong ownership from architecture to production operations. Engineers work with AI tooling and cloud infrastructure to deliver reliable, secure, and maintainable systems in a high-growth environment. 🗂️ Requirements: Senior-level backend engineering experience, Strong Python skills, Experience designing production backend systems, Knowledge of distributed systems, Experience with concurrency and async processing, Hands-on cloud infrastructure experience, Database schema design expertise, Performance tuning for high-throughput systems, Security-conscious engineering approach, Ability to own systems from design to production, Clear written and verbal communication, Experience using AI tools in engineering workflows, Ability to work from Warsaw office 📃 Skills: Python, AWS, GCP, Azure, TypeScript, Codex, Claude, Copilot, APIs, LLM 🏢 Description: About Shelf The enterprise is going agentic and we are creating a unique operating system for an automated future. Most AI agents break the moment they hit real business complexity. That’s why we built a platform that models a company's policies, workflows, and operational logic into an AI Data Model. Shelf enables AI Agents to reliably reason and deliver precise and reliable outcomes at scale. We already have what most AI startups are still trying to earn: Enterprise customers such as Glovo, Nespresso, and HelloFresh, real production data, and tens of thousands of users. Customers trust us with operational knowledge: Our platform is highly reliable and secure with SOC2, HIPAA-ready security practices, and mature integrations in place. Job Description: This role is for a senior backend engineer who can design and own business-critical systems. We want someone who is strong technically, communicates clearly, and has the judgment to make systems simpler, safer, and easier to evolve over time. Expect real ownership from system design through production. The team is small enough for engineers to make real decisions. Career growth comes from ownership. Titles matter less than the scope you can carry. The people who grow fastest take responsibility for larger systems, drive customer outcomes, and strive to develop better engineering practices. You solve ambiguous problems by shaping the right architectural approach, then ship, iterate, and keep it healthy in production. We build AI-native. Engineers use Codex, Claude Code, and agents they build themselves. We invest in harness engineering through skills, CLIs, logs, traces, and orchestration. This is a role for someone in a high-growth chapter of their career, who wants to do the best work of their life, learn fast, and win as part of a team going all-in on a hard mission. Location – Warsaw, work from the office. What You Will Own Design and ship backend services, APIs, data flows, and background processing for production systems Turn vague requirements into concrete technical plans, trade-offs, and execution Own services after launch: reliability, observability, performance, and incident follow-through Instrument what you ship and use production signal to iterate, not just to keep the lights on Make sound decisions around system boundaries, data models, interfaces, and scaling paths Work closely with product, frontend, and platform engineers to deliver end-to-end outcomes Improve engineering leverage with AI tooling, automation, and internal workflows rather than using AI as a gimmick Raise the quality bar through code review, design review, and pragmatic technical leadership What Strong Performance Looks Like You reliably move important backend work forward without waiting to be tightly managed. Your systems are easier to operate and easier to change because of your design decisions. You make smart trade-offs to unblock shipping - and you stand by those decisions. You keep raising the bar on engineering excellence for yourself and everyone else. What We Are Looking For Strong senior-level backend engineering experience in production systems Strong Python skills and the ability to design clean, maintainable backend code Good distributed systems judgment: concurrency, failure handling, data consistency, async work, and service boundaries Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure Comfort with database schema design and performance tuning for real-time and high throughput scenarios A security-conscious approach to engineering: you build for enterprise-grade requirements, handle sensitive data carefully, and think about the security implications of the systems and AI workflows you ship Ability to go from problem statement to design to production rollout with real ownership Clear written and verbal communication. You can explain systems, trade-offs, and incidents without hiding behind jargon AI-native working style. You already use AI tools in your daily engineering workflow, and you're excited to improve how the team builds, not just your own output: better tooling, workflows, and engineering leverage Strong Plus Experience building agentic systems: AI agents, tool-calling, orchestration, retrieval, or LLM-backed infrastructure in production Working knowledge of TypeScript or the ability to contribute across the stack when needed Experience shaping technical direction for other engineers, even without formal management responsibility How We Evaluate Fit We care more about ownership, systems judgment, and learning velocity than a perfect keyword match to our stack. If you are the kind of engineer who can take a messy problem and turn it into a strong production system, we want to talk. What Shelf Offers: B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. A strong AI-native engineering environment with modern tools and room to experiment, including Claude Code, OpenAI Codex, and GitHub Copilot. Why Shelf: Becoming one of the defining companies of the AI age is a hard plan, and our leadership team has the rare mix of deep AI, knowledge-management, and enterprise SaaS experience to actually execute it We have raised over $60 million in funding; our investors include Tiger Global, Insight Partners, Base10, and others Recognized by Gartner as a Cool Vendor, with high-velocity growth powered by the most innovative product in our category We love our customers and our customers love us. Ask a Shelf customer why, and they'll tell you it's our innovative capabilities and rock-solid reliability, that they enjoy working with our people, and most of all, the improvements they see in their business KPIs We're building fast across three hubs: our New York HQ and our Product and Engineering centers in Warsaw and Lviv

🏢 Summary: Hands-On Engineering Manager role focused on building and shipping AI-native, agentic banking products that operate across voice, chat, and digital channels. The position involves architecting low-latency distributed backend systems, orchestrating multi-agent LLM workflows, and leading a high-performance engineering team while remaining deeply hands-on. The goal is to deliver production-grade AI systems that autonomously power real-time financial customer experiences. 🗂️ Requirements: 8+ years backend engineering experience, Experience building distributed systems, Experience with low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating systems with LLMs, 2+ years engineering management or technical leadership experience, Experience designing and orchestrating agentic workflows, Proficiency in Typescript and/or at least two backend languages, Strong understanding of distributed systems, concurrency, reliability, Experience deploying AI systems in cloud environments, Experience building high-concurrency, fault-tolerant systems, Experience implementing observability, monitoring, and testing for production systems, Experience ensuring security and safe handling of financial data 📃 Skills: Typescript, Node.js, Go, Java, Rust, LLM, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, Chat, APIs, Cloud, Observability, Monitoring, Testing, Security, ReinforcementLearning, MultiAgentSystems 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Hands-On Engineering Manager role focused on building and orchestrating AI-native, agentic systems for real-time voice and chat in banking. The position combines deep backend distributed systems expertise with LLM-driven multi-agent architectures to deliver low-latency, production-grade AI products. You will lead a high-performance team while remaining hands-on in architecting and shipping scalable, reliable AI systems. 🗂️ Requirements: 8+ years backend engineering experience in distributed systems, Experience building low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating and orchestrating LLMs, 2+ years engineering management or technical leadership experience, Strong proficiency in TypeScript and/or at least two backend languages (Node.js, Go, Java, Rust), Deep understanding of distributed systems, concurrency, and reliability, Experience deploying AI systems in cloud environments, Experience designing agentic workflows and multi-agent systems 📃 Skills: TypeScript, Node.js, Go, Java, Rust, LLMs, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, APIs, Cloud, ReinforcementLearning, Monitoring, Observability 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.