Land Acquisition Manager

🏢 Summary: Own and drive land acquisition, surface rights negotiations, and lease analysis to secure critical sites for AI infrastructure development. Lead financial modeling, underwriting, and contract review while coordinating cross-functional teams and third parties to move projects from site selection through deal execution. This high-visibility, onsite role directly shapes real estate strategy and development pipeline execution. 🗂️ Requirements: Ability to negotiate and draft land agreements, surface use agreements, ROW/easements, Strong knowledge of lease structures, title, surveys, permits, access rights, development economics, contract interpretation, Experience reviewing and analyzing complex contractual language and risk provisions, Ability to synthesize large datasets into actionable recommendations for senior stakeholders, Experience coordinating third parties and managing multiple concurrent transactions, Proficiency in Microsoft Office, Proficiency in Google Workspace 📃 Skills: Negotiation, RealEstate, Leases, Contracts, Underwriting, FinancialModeling, Zoning, Surveys, Title, Microsoft, Google 🏢 Description: What you'll do As Land Acquisition Manager, you will own land acquisition, surface rights negotiation, and lease analysis that drives critical real estate decisions in AI infrastructure. You will work directly with landowners, surface holders, and third-party brokers to secure sites that power the development pipeline, while partnering with legal, finance, and operations to structure deals and keep projects moving. This is a high-visibility role where your work directly shapes where and how projects are built. Where you'll work This is an in-office role ideally based in the Houston office, with full-time onsite expectations outside of bi-weekly work-from-home Fridays. Exceptions may be considered for exceptional candidates. Responsibilities - Track and manage an active pipeline of real estate and land opportunities, maintaining deal status, key milestones, and financial summaries across multiple concurrent transactions - Identify, contact, and negotiate directly with surface owners and landowners to secure access agreements, ROW/easements, ground leases, and purchase contracts - Review, interpret, and summarize lease and contract language, identifying provisions that impact site access, development rights, operational constraints, and financial obligations - Conduct market research and comparable analyses to evaluate site values, rental rates, and land market dynamics in target geographies - Lead financial modeling and underwriting for land acquisitions, ground leases, and build-to-suit developments - Support site selection by synthesizing zoning, entitlement risk, infrastructure constraints, and financial feasibility into clear investment recommendations - Coordinate third-party surveyors, field brokers, and contractors; accompany teams to the field as needed to support site assessment and due diligence - Collaborate with legal, development, and operations teams to review LOIs, PSAs, surface use agreements, and lease agreements, ensuring economic terms align with underwriting assumptions - Maintain accurate land and lease records, deal documentation, and pipeline reporting - Serve as a point of contact for landowner relationships, resolving issues and managing ongoing obligations on the active asset base Requirements - Demonstrated ability to negotiate and draft land agreements, surface use agreements, ROW/easements, or similar instruments - Strong working knowledge of real estate and land fundamentals: lease structures, title, surveys, permits, access rights, development economics, and contract interpretation - Experience reviewing and analyzing complex contractual language, identifying key obligations and risk provisions - Demonstrated ability to synthesize large amounts of data and present clear, actionable recommendations to senior stakeholders - Comfortable coordinating third parties in the field and managing multiple concurrent workstreams under time pressure - Proficiency in Microsoft and Google suites Benefits - Subsidized health, dental, and vision insurance - Equity (options) - 401(k) with 4% employer match - Unlimited PTO - Parental leave - Healthcare and Dependent Care FSA or HSA - Commuter benefits

🏢 Summary: Engineering leadership role to build and scale an AI Labs team developing autonomous AI agents for enterprise commerce. Responsible for defining the architecture, shipping production-grade agentic AI systems, and driving AI-assisted development at startup speed within a pre-IPO environment. The role combines hands-on technical direction with ownership of infrastructure, quality, and engineering execution. 🗂️ Requirements: Proven experience building and scaling high-performing engineering teams, Hands-on expertise in software architecture and system design, Experience shipping AI or LLM-based products to production, Deep knowledge of LLM orchestration and agent architectures, Experience with AI-assisted development tools in engineering workflows, Ownership of infrastructure efficiency, reliability, and product quality metrics, Ability to operate at startup pace with rapid release cycles, Onsite presence in Mountain View, CA 📃 Skills: LLMs, GPT-4, Claude, AgenticAI, Architecture, Orchestration, AIDevelopment, Cursor, OpenSource, Infrastructure, DistributedSystems 🏢 Description: CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week. 2,200+ Customers 10 of Top 12 CPG Companies 900+ Retailers Connected $200M+ Raised Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.The Problem: We have thousands of enterprise users, proven product-market fit across digital shelf analytics, retail media, and sales operations, and the Fortune 100 running on our platform. That part works. Now we are building something new: autonomous AI agents that are already in customer hands and scaling fast. This is a 0-to-1 build inside a company that has the distribution, the data, and the customers to make it real. The AI Labs team operates as a startup within the company. It needs its own engineering leader. Someone who can recruit a world-class team in Mountain View, set the technical direction for agentic AI in commerce, and ship at a pace that matches the opportunity. We have engineering teams across the US, India, Canada, and the UK. Mountain View is the center of gravity for AI leadership. This role reports directly to the Founders. We ship with Claude, GPT-4, and open-source models in production. Our engineers already write the majority of code with AI. Some things are great. Some things need to be rebuilt. The next leader will know the difference. What You'll Do: Build the Future of Commerce AI Architect and evolve the platform for the agentic era. The technical foundation needs to support agents that operate autonomously across content, media, and sales. You will decide what gets built, how it gets built, and what gets thrown away. Push the frontier on AI-assisted development. We already lead most companies in AI code contribution. Claude Code, Cursor, and the next generation of agentic dev workflows should be standard across the org. As a startup, we should be ahead of everyone else on this. Ship AI agents into production with speed and reliability. Our agents are already in Fortune 100 workflows and scaling fast. Engineering needs to deliver new capabilities on a weekly cadence. Be the technical face of the company externally. Our AI Brand positioning depends on engineering leaders who can speak credibly about what we are building. Conference talks, blog posts, recruiting events. Build the Team Recruit and retain world-class engineering talent, starting with Mountain View. You will be measured on the quality of people you bring in and the quality of people you develop. Build a strong engineering leadership bench. We need senior leaders who can independently own large surface areas and represent engineering with authority across the company. Create an environment where the best engineers want to stay, grow, and recruit their friends. Every hire should raise the average. Own Engineering Execution Own product quality, infrastructure efficiency, and engineering velocity. You set the metrics, you hit them. Drive continuous improvement in margins and cost structure. We have already made dramatic improvements in infra costs and product reliability. You will own the next chapter. What You'll Bring: This is not a caretaker role. We need a builder. Here is what matters: You have built and scaled engineering teams. You have taken a team from good to great. You know how to hire senior talent, develop middle managers, and create a culture where A-players attract more A-players. Ideally you have done this at a pre-IPO company scaling through a similar inflection point. You are technical and hands-on. You can go deep on architecture discussions, review technical designs, and earn the respect of senior engineers. You do not need to write code every day, but you need to be able to tell when code is good and when it is not. You are AI-native. You personally use AI development tools. You have opinions about LLM orchestration, agent architectures, and how AI changes the software development lifecycle. You are excited about a world where AI writes most of the code and engineers focus on architecture, judgment, and customer impact. You operate with urgency. Startup pace. Weekly shipping cadence. You do not tolerate multi-month planning cycles for things that should take days. You bias for action and course-correct fast. You are a talent magnet. The best engineers you have worked with want to work with you again. You have a network of strong technical leaders you can bring in. You know the difference between hiring for pedigree and hiring for signal. You want to be in the room. This is an onsite role in Mountain View. You will work closely with the Founders, product, and customer success. Our best decisions happen face-to-face. Compensation and Benefits: Base: Competitive with top-tier Silicon Valley companies. Commensurate with experience. Equity: Significant pre-IPO stock options. This is a leadership seat and the equity reflects that. We are at a stage where senior hires still get meaningful ownership. Benefits: Full medical, dental, vision. 401(k). Unlimited PTO. Location: Mountain View, CA. Onsite. 15 minutes from Stanford campus. Why Join Now: The window is now. The company has product-market fit, revenue, and customers. The AI Labs team is being built right now. In 12 months this team will be set. The founding members will define the culture, the architecture, and the trajectory. This is that moment. Real AI, not AI theater. Most companies are bolting AI onto legacy products and calling it innovation. We are rebuilding the entire platform around autonomous agents. Our agents are already in production, already in customer workflows, already making decisions. If you want to lead a team doing real AI, this is it. Fortune 100 scale. Your decisions will directly affect how 2,200+ brands run their ecommerce. The Fortune 100 uses our platform to manage billions of dollars in commerce. This is not a sandbox. Equity upside. Pre-IPO. $200M+ raised from tier-one investors. The economics of joining at this stage, in this role, are compelling. Check out our LinkedIn page to learn more about what it’s like to work at CommerceIQ!We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.

🏢 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.

🏢 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: Strategic Technical Product Manager (Data & AI) role owning the roadmap for customer-facing AI/ML models and data products in a SaaS environment. You will partner with executive clients to co-develop predictive features, translate business problems into technical specifications, and launch high-impact analytics solutions. This role sits at the intersection of data science, engineering, and go-to-market execution, driving measurable ARR growth. 🗂️ Requirements: 3+ years experience in Product Management, Data Analytics, or Data Engineering, Strong SQL skills (joins, aggregations), Experience with modern BI platforms (Sigma, Tableau, or Looker), Ability to translate business problems into technical data requirements, Experience working with AI/ML models or advanced analytics features, Strong understanding of SaaS product metrics and customer ROI 📃 Skills: SQL, Sigma, Tableau, Looker, Snowflake, DBT, Fivetran, Python, R, AI, ML, SaaS, Analytics, Data, Visualization 🏢 Description: We aren’t just looking for someone to manage a backlog; we’re looking for the founding architect of our customer-facing data and AI strategy. As a Technical Product Manager (Data & AI), you will sit at the intersection of Data Science, Engineering, and customer-facing value. This is a highly visible, strategic role where you’ll partner directly with executive-level clients to co-develop predictive models, analytical features, and SaaS data products. WHAT YOU'LL DO Shape the AI & Data Vision - Own the predictive roadmap for external AI/ML models, advanced analytics features, and data products - Co-innovate with strategic customers and design partners to validate ideas and uncover user needs - Partner with UX and Data Science to translate complex algorithms into intuitive data visualizations and impactful demos Execute & Ship with Impact - Translate customer business problems into technical specifications, transformation logic, and data requirements - Collaborate with Product Marketing and Sales to launch features that drive adoption, retention, and ARR expansion - Use data analysis to validate assumptions and test product hypotheses before development WHAT YOU’LL BRING - 3+ years of experience in Product Management, Data Analytics, or Data Engineering - Strong business and product acumen with ability to connect technical features to customer ROI - SQL fluency, including writing joins and aggregations - Experience with modern BI platforms such as Sigma, Tableau, or Looker - Ability to communicate effectively with executive clients, sales teams, engineers, and data scientists NICE TO HAVE - Experience with modern data stack tools such as Snowflake, DBT, Fivetran, and Sigma - Familiarity with Python or R for lightweight data analysis - Exposure to machine learning lifecycle or productionized models - Experience in complex B2B SaaS industries BENEFITS - Health and dental insurance - 401k with company match - Flexible Time Off or generous PTO plan - Paid holidays and up to 4 weeks paid bonding leave - Tuition reimbursement - Employee Assistance Program - 24/7 virtual medical care access

🏢 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: Leadership role to build and scale a 0→1 ML/AI platform enabling large-scale model training and inference across the organization. The position drives technical vision, roadmap, and organizational structure while overseeing multiple teams and managers. It covers the full AI lifecycle, from training and serving to deployment and monitoring, using open-source tooling. 🗂️ Requirements: Experience building 0→1 ML/AI platforms, Hands-on experience with open-source ML infrastructure (e.g., Ray, AnyScale), Strong technical background in large-scale training and inference systems, Experience managing managers and leading multiple engineering teams, Proven record of delivering production-grade AI systems, Experience defining technical vision and roadmap for AI platforms, Experience supporting full AI lifecycle: training, serving, deployment, monitoring 📃 Skills: Python, Ray, AnyScale, ML, AI, OpenSource, Training, Inference, Deployment, Monitoring, Infrastructure, Platforms 🏢 Description: The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI, LLMObs and all our AI research. You’ll join a new and fast growing team that is critical to the future of Datadog. You will support building and scaling the team, help define our technical vision and help shape the roadmap. You will manage other managers and help define the future structure of our organization, participating in the recruitment of the future managers and ICs of the department. You’ll work closely with partner teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org, product engineering teams, and Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Lead a fast-growing organization around 20 people across 2 teams soon to be 3. You will define the roadmap for your scope and work with ICs and managers to establish the technical direction Collaborate with the engineering team and product manager to define the future of the roadmap Create a strong organizational culture centered around our engineering standards and customer- focused approach Support the whole lifecycle of AI development, including model training, serving, deployment and monitoring Who You Are: You’ve led teams that have built 0 to 1 ML/AI Platforms, with an emphasis on Open Source Tooling (i.e. Ray / AnyScale), versus pure out-of-the-box solutions. An experienced engineer and team player with strong technical skills to influence the technical direction of your teams A people leader with strong interpersonal skills, who has built and led high-performing software engineering teams, including managing managers Interested in working on an early stage project with many challenges to solve and a fast iteration cycle. You bring a strong bias for delivery and make impact through ambiguity. You have a track record of delivering high-quality software on schedule and collaborating closely with product partners. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: New hire stock equity (RSUs) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Intradepartmental mentor and buddy program for in-house networking An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) Access to Inclusion Talks, our Internal panel discussions Free, global mental health benefits for employees and dependents age 6+ Competitive global benefits Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$234,000—$300,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.