Forward Deployed Engineer - GTM

🏢 Summary: Staff Forward Deployed Engineer responsible for designing and deploying advanced agent-based AI and RAG solutions using the Workato Agentic AI platform. The role focuses on building scalable, autonomous AI workflows, integrating enterprise systems, and delivering tailored AI-driven automation solutions for customers. It combines AI engineering, integration architecture, and hands-on development in complex enterprise environments. 🗂️ Requirements: BTech/BE or higher in Computer Science, AI, ML, or related field, 12+ years experience in design, development, and implementation, Minimum 1 year hands-on experience with Workato, Proven experience in AI engineering with agent-based systems, Experience designing and implementing scalable AI-driven workflows, Hands-on experience in integration projects and automation technologies, Strong knowledge of RESTful and SOAP/XML APIs, Strong understanding of JSON and data structures, Experience with RDBMS or NoSQL databases, Hands-on programming experience in Java or Python or Ruby 📃 Skills: Workato, AI, MachineLearning, LLM, RAG, APIs, REST, SOAP, JSON, RDBMS, NoSQL, Java, Python, Ruby, Microservices, SOA, ESB, BPM, RPA, iPaaS, SaaS, Cloud, TIBCO, MuleSoft, DellBoomi, Workday, NetSuite, Salesforce, ServiceNow, Marketo 🏢 Description: About Workato Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an experienced Staff Forward Deployed Engineer to join our Forward Deployed Engineering team. In this role you will be responsible for designing, developing, and deploying advanced AI Agentic Solutions that exhibit autonomous, proactive, and adaptive behaviors. This role requires a deep understanding of AI/ML technologies, integration, automation experience, and solution architecture, combined with strong problem-solving skills and the ability to collaborate across multidisciplinary teams. Workato has a positive, diverse, and collaborative culture—we look for people who are curious, inventive, smart, hardworking, and work to be a little better every day. Workato has also been recognized amongst the “Top 47 Enterprise Startups to Bet Your Career On in 2020”, the “Hottest 13 Productivity Software Startups to Watch in 2020!”, and the “Top 15 Startups helping even non-programmers build simple apps, ahead of an expected software developer shortage” by Business Insider. In this role, you will also be responsible for: Implement agent-based AI solutions using the Workato Agentic AI platform Implement intelligent, autonomous, and efficient agentic AI workflows that utilize multi-agent collaboration, orchestration, and the automation capabilities provided by the Workato platform Implement and deploy Retrieval-Augmented Generation (RAG) systems using Workato’s Agentic AI capabilities, leveraging its connectors, workflows, and recipes to enable context-aware, grounded, and real-time responses from large language models (LLMs) Develop advanced prompting, memory management, and behavior-planning techniques to enable LLMs and agents to reliably author and execute complex workflows Act as a technical solutions expert with strong aptitude in troubleshooting and analyzing AI-driven architectures, including scalable RAG pipelines and agent frameworks built using the Workato Agentic AI platform Develop and maintain robust, scalable AI-powered IT workflows with agent-based decision-making, dynamic retrieval mechanisms, and seamless integration using the Workato Agentic AI platform Continuously monitor and improve AI system performance, ensuring efficiency and reliability Work closely with customers to understand use cases and deliver tailored, scalable agentic AI and RAG-based solutions using the Workato Agentic AI platform, while prioritizing exceptional customer service to ensure alignment with both technical and business needs, as well as satisfaction and successful implementation Collaborate with cross-functional teams to integrate AI workflows into existing IT frameworks, ensuring smooth and seamless deployment Contribute to internal process improvements and promote knowledge sharing by adding to Workato’s knowledge base Play an instrumental role in all phases of product development, from ideation to implementation, contributing valuable insights and expertise Assist the Product Manager in creating technical and design specifications, ensuring alignment with product goals and user needs Leverage strong communication skills to effectively translate complex technical concepts into accessible insights for non-technical audiences Requirements Qualifications / Experience / Technical Skills BTech/BE or higher technical education in Computer Science, Artificial Intelligence, Machine Learning, or a related field A total of 12+ years of relevant experience in design, development, and implementation, with at least 1 year of experience in Workato, is a must Proven experience in AI engineering, with a focus on agent-based systems Demonstrated ability to design and implement scalable AI-driven workflows that enhance IT operations Knowledge of implementing integration projects is essential. Hands-on experience with automation technologies, middleware, integration architecture patterns, web services technologies, enterprise messaging patterns, APIs, SOA, ESB, BPM, SDKs, and databases Experience working with integration platforms such as Workato, TIBCO, Dell Boomi, MuleSoft, or other integration/automation tools is a plus. Experience with cloud technologies—iPaaS, SaaS applications, and cloud infrastructure—is also a plus Strong working knowledge of APIs—RESTful, SOAP/XML. Solid understanding of data structures—JSON. Sound knowledge of any RDBMS/NoSQL Hands-on experience with any of the following: Java, Python, or Ruby Technical background or a solid understanding of technology and industry trends, especially in the app integration space Experience working with cloud business apps like Workday, NetSuite, Salesforce, ServiceNow, Marketo is a plus Good knowledge of Microservices or API-based integration architecture, event-driven architecture, and process automation via BPM or RPA is a plus Soft Skills / Personal Characteristics Strong collaboration skills, ability to adapt to a dynamic startup environment with a passion for making an impact Strong critical thinking, analytical skills with an entrepreneurial and proactive mindset Ability to effectively prioritize tasks and manage time, even under high-pressure situations Strong written and oral communication skills in English, with the ability to convey complex technical concepts effectively to a non-technical audience Fast learner who can independently conduct extensive research, and synthesize ideas, information and options quickly Be proactive about solving problems and be ready to take on additional initiatives and responsibilities as they emerge (REQ ID: 2447)

🏢 Summary: Mid Full Stack Engineer role focused on building and improving AI-powered enterprise products across frontend and backend systems. The position involves developing web applications, APIs, and production features using modern technologies while collaborating closely with cross-functional teams. Candidates will work with AI development tools and contribute to scalable, high-quality software in a fast-growing environment. 🗂️ Requirements: 2–5 years of experience building production web applications, Knowledge of React, Knowledge of TypeScript or another modern frontend framework, Experience building backend services, Experience building REST APIs, Familiarity with testing and version control, Understanding of web application architecture, Understanding of client-server communication, Problem-solving skills, Attention to code quality, Strong communication skills, Experience using AI development tools, Willingness to collaborate across engineering, product, and design teams 📃 Skills: React, TypeScript, REST, Git, GitHub, Copilot, Claude, ChatGPT, Python, Node.js, AWS, GCP, Azure, Docker, CI/CD 🏢 Description: About Us Many companies want to use AI agents, but these agents often struggle with complex business tasks. We solve this problem by building a platform that understands company knowledge, policies, processes, and workflows, enabling AI to make reliable decisions instead of simply generating answers. Our technology helps businesses automate up to 85% of customer cases, reduce handling time by 20–25%, and complete tasks that previously took hours in just a few seconds. Our mission is simple: to give people better answers everywhere. About the Role We are looking for a Mid Full Stack Engineer who enjoys building products and solving real user problems. In this role, you'll work across both the frontend and backend, collaborating closely with engineers, product managers, and designers to deliver new features and improve existing ones. You'll have the opportunity to work with modern AI technologies, contribute to production systems, and grow your technical skills in a fast-moving environment. If you enjoy learning, shipping high-quality software, and working on products used by enterprise customers, we'd love to hear from you. Responsibilities - Build and maintain product features across both frontend and backend. - Develop user interfaces using modern frontend technologies. - Build and extend backend APIs and business logic. - Collaborate with engineers, product managers, and designers to implement new functionality. - Improve application performance, reliability, and usability. - Write clean, maintainable, and well-tested code. - Participate in code reviews and engineering discussions. - Help monitor production systems and improve features based on user feedback and product data. - Use AI development tools to improve productivity and software development workflows. Requirements - 2–5 years of experience building production web applications. - Good knowledge of React, TypeScript, or another modern frontend framework. - Experience building backend services and REST APIs. - Familiarity with modern software engineering practices, testing, and version control. - Understanding of web application architecture and client-server communication. - Good problem-solving skills and attention to code quality. - Strong communication skills and willingness to collaborate across engineering, product, and design teams. - Experience using AI tools such as GitHub Copilot, Claude Code, ChatGPT, or similar in day-to-day development. - Curiosity, ownership of your work, and a desire to continuously learn. Nice to Have - Experience with Python, Node.js, or both. - Experience working on AI-powered products or LLM integrations. - Familiarity with cloud platforms (AWS, GCP, or Azure). - Knowledge of Docker, CI/CD, or modern deployment workflows. - Understanding of performance optimization and accessibility best practices. What We Offer - B2B contract. - Company stock options. - MacBook Pro for work. - Modern technology stack with opportunities to contribute to open-source projects. - Access to advanced AI development tools, including GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, and MCP Servers. - The opportunity to work on real AI products used by enterprise customers. - A collaborative engineering culture focused on learning, ownership, and continuous improvement. - The chance to grow your career alongside experienced engineers in a fast-growing AI company. Why Join Us Our leadership team brings deep experience in AI and knowledge management. We've raised over $60 million in funding and achieved three consecutive years of 3× growth. We believe great products are built by great teams, and our culture is shaped by these values: - Quality - We care about craftsmanship and building software that lasts. - Momentum - We move quickly, iterate often, and continuously improve. - Accountability - We take responsibility for our work, communicate openly, and support one another. - Hard Work - We believe ambitious goals require dedication and teamwork. - Learning Agility - We stay curious, embrace feedback, and continuously develop our skills. - Adapt and Thrive - We welcome change and see challenges as opportunities to improve. - Win Together - We succeed by collaborating, sharing knowledge, and helping each other grow.

🏢 Summary: Site Reliability Engineer role focused on leading the cloud platform layer of a large-scale enterprise migration to GCP, with full ownership of observability and FinOps capabilities. The position involves architecting cost attribution, distributed tracing, monitoring, and performance engineering solutions in a production-grade Kubernetes environment. You will work on complex distributed systems, extending multi-language codebases and managing infrastructure as code in a regulated enterprise setting. 🗂️ Requirements: 4–6 years software or DevOps engineering experience, 2–3 years hands-on cloud infrastructure management in production, Strong GCP expertise including GKE and Cloud Run, Proven experience building observability solutions with OpenTelemetry, Experience with distributed tracing and profiling in distributed systems, Advanced Python scripting for automation and tooling, Strong Terraform proficiency with multi-environment setups, Ability to read and modify Kotlin and Java codebases, Experience implementing monitoring, alerting, and SLOs for containerized/serverless services, Experience with infrastructure cost attribution and cloud billing APIs 📃 Skills: GCP, GKE, CloudRun, Kubernetes, OpenTelemetry, Terraform, Python, Kotlin, Java, FinOps, PubSub, Bigtable, Docker, SLO, Tracing 🏢 Description: We are looking for a Site Reliability Engineer to join a high-stakes global tech ecosystem and drive the delivery of a critical enterprise platform migration to the cloud. Your core mission will be to architect, build, and productionalize the observability and cost intelligence (FinOps) layer for a massive, multi-year financial platform transformation. You will take end-to-end ownership of the cloud platform layer, giving internal stakeholders full visibility into platform behavior, performance, and infrastructure spend. Working alongside a nearshore team of senior engineers, you will solve highly complex architectural challenges in a production-grade, distributed system. Responsibilities: End-to-End Infrastructure & FinOps Ownership: Architect and implement a cloud usage and cost attribution dashboard, providing detailed per-pod and per-service cost breakdown using cloud billing APIs and internal FinOps hubs. Advanced Observability & Tracing: Instrument end-to-end distributed tracing using OpenTelemetry, configuring collectors within Kubernetes environments and exporting traces to cloud monitoring systems utilizing RED metrics. Performance Engineering & Stress Testing: Write custom tooling from scratch to deliver database performance monitoring, load testing, and trend analysis for critical underlying storage layers. Monitoring & Alerting Automation: Build and deploy scalable production monitoring, custom alerting policies, and SLO tracking for containerized and serverless services. Infrastructure as Code: Independently manage, write, and apply infrastructure modifications using Terraform, working within established enterprise repository standards, modules, and environment state management. Cross-Language Codebase Extension: Read, debug, and extend existing platform code across a diverse stack including Kotlin, Java, and Python to seamlessly integrate technical metrics without disrupting business logic. Quality & Release Assurance: Implement rigorous unit testing with high code coverage for all newly developed monitoring tools to comply with strict enterprise quality gates and sign-offs. Min requirements: Experience: 4 to 6 years of professional software or DevOps engineering experience, with at least 2 to 3 years of hands-on cloud infrastructure management in production. Advanced Cloud Infrastructure: Deep operational proficiency with Google Cloud Platform (GCP), specifically with managing and configuring workload-level alerting on Google Kubernetes Engine (GKE) and Cloud Run. Observability & OpenTelemetry: Proven track record of building observability solutions in distributed systems, using OpenTelemetry (both auto and manual instrumentation) alongside distributed tracing and profiling tools. Strong Automation Scripting: Intermediate-to-advanced fluency in Python for writing custom test tooling, metrics integration scripts, and backend automation from scratch. Solid Infrastructure as Code: Strong proficiency in Terraform, including experience with multi-environment setups, workspaces, and corporate module standards. Polyglot & JVM Familiarity: Practical ability to read, understand, and modify existing backend codebases written in Kotlin and Java. Crucial Non-Technical Skills: Extreme technical autonomy to resolve blockers independently, rapid onboarding skills into large unfamiliar codebases, and fluent written English for async alignment and pull requests. Process Alignment: Ability to thrive in a highly regulated enterprise environment with strict peer reviews, robust documentation requirements, and formal deployment procedures. Would be a plus: Domain Knowledge: Previous experience working within financial services, fintech, investment banking, or other highly regulated industries. Enterprise Streaming Tools: Working knowledge of cloud messaging systems (such as Cloud Pub/Sub) utilized for inter-service communication. Advanced Storage Engines: Familiarity with high-throughput distributed database architectures, such as Google Cloud Bigtable. Systems Languages Awareness: Ability to read or debug foundational code written in low-level systems languages like Rust or C++ during multi-stack production deployments. We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Frontend engineering role focused on building enterprise-grade Next.js interfaces for AI-powered systems, including real-time AI interactions, semantic search, and knowledge-driven workflows. The position involves developing scalable, accessible, and high-performance UIs while contributing to frontend architecture, design systems, and AI-assisted engineering workflows. Candidates will work with modern AI tooling and enterprise application requirements in a fast-growing product environment. 🗂️ Requirements: 3–5 years frontend engineering experience, React expertise, TypeScript expertise, Production Next.js experience, SSR/SSG/CSR knowledge, State management experience, Experience with AI/LLM interfaces, Frontend performance optimization knowledge, Core Web Vitals understanding, Localization experience, Accessibility knowledge, Security best practices knowledge, AI coding assistants usage, Clear technical communication 📃 Skills: React, TypeScript, Next.js, SSR, SSG, CSR, JavaScript, LLM, AI, CoreWebVitals, Localization, Accessibility, Security, ReactFlow, Highcharts, RAG, MCP, DSPy, Node.js, Python, GitHubCopilot, Codex 🏢 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. About the Role This role is for a frontend engineer with a few years of experience who wants to craft the interfaces that make enterprise AI accessible and trustworthy. While others build chatbots, we're solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability? You'll build production Next.js applications that handle complex state, real-time AI streaming, and real enterprise functionality, growing into the harder architectural calls over time. We obsess over frontend quality because we're building the trust layer for AI itself: when your interfaces handle edge cases gracefully, give clear feedback during AI processing, and stay fast under load, you directly enable users to trust AI-powered answers and make critical business decisions. In our environment, AI isn't just what we build, it's how we build. You'll work alongside engineers who use AI coding assistants daily, build custom MCP servers, and experiment with new AI tooling to move faster. 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. What You Will Own Build and ship production Next.js applications with complex state and real-time AI interactions Build interfaces for AI-powered features: streaming LLM responses, semantic search, interactive knowledge graphs, and agentic builders Contribute to the component library and design system, keeping things reusable, accessible, and consistent Deliver enterprise-grade functionality: localization, accessibility, cross-browser support, and security best practices Help own what you ship after launch: monitor performance, optimize bundle sizes, and keep an eye on Core Web Vitals Use AI tools daily to move faster, and help improve internal frontend workflows Keep the bar high on code quality and testing through thoughtful code review What Strong Performance Looks Like You turn vague product problems into shipped, well-reasoned interfaces that users trust Complex AI behavior feels legible and controllable to users because of how you built the UI Your components are reusable, accessible, and perform well under real load You bring momentum. Work moves because you are on it What We Are Looking For Around 3 to 5 years of frontend engineering experience, with strong React and modern TypeScript Production Next.js experience: you've built and shipped SSR applications and understand the trade-offs between SSR, SSG, and CSR, with the appetite to go deeper Solid state management, with exposure to harder scenarios (real-time updates, optimistic UI, multi-tenant data) and the drive to grow there Experience building or contributing to AI/LLM interfaces: streaming responses, chat UIs, semantic search, or similar A feel for frontend performance: you care about Core Web Vitals and know the basics of improving them Exposure to enterprise application concerns: localization, accessibility, and security best practices A security-conscious approach to engineering: you handle sensitive data carefully and think about the security implications of what you ship Strong craft and product instinct: you spot UX issues and propose solutions, and you're not satisfied with "good enough" AI-native working style. You already use AI coding assistants daily and are eager to push the boundaries of AI-assisted development Clear communication. You articulate design decisions and technical trade-offs clearly, verbally and in writing Strong Plus Experience with React Flow, Highcharts, or other complex data-visualization libraries Hands-on experience with vector search UIs, RAG interfaces, or semantic search Familiarity with MCP, DSPy, or other cutting-edge AI frameworks, and building agentic AI interfaces Understanding of Node.js/Python backend fundamentals: you can read backend code and follow API design discussions Contributed to design systems or open-source component libraries A track record of growing fast and taking on more than your title strictly required How We Evaluate Fit We care more about craft, ownership, and the ability to make complex AI feel trustworthy than a perfect match to every library on paper. If you are the kind of engineer who can take a messy, complex enterprise problem and turn it into an interface people trust, we want to talk. What Shelf Offers B2B contract Company stock options Hardware: MacBook Pro Modern technical stack. Develop open-source software 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 DevOps/Cloud Engineer role focused on designing and operating cloud infrastructure and data platforms for a Forbes 500 private equity client. The position involves owning AWS-based environments, Infrastructure-as-Code, Kubernetes workloads, identity and authentication systems, and production reliability. You will support data engineering teams by building secure, scalable, and observable multi-cloud infrastructure. 🗂️ Requirements: 10+ years in IT, 5+ years in DevOps/Cloud role, Deep AWS expertise (IAM, EC2, S3, EKS), Strong Terraform experience with end-to-end IaC ownership, Hands-on Kubernetes setup and operations, Docker proficiency, Strong Python skills, Strong Bash skills, Experience with IAM and identity providers, Knowledge of OAuth/OIDC and SSO, Experience with Entra ID and Active Directory, Observability and SRE practices experience, Experience with relational and NoSQL databases, C1+ English proficiency 📃 Skills: AWS, Azure, Terraform, Python, Bash, SQL, Docker, Kubernetes, Airflow, Snowflake, Redshift, Athena, GitLab, Artifactory, SQLAlchemy, IAM, OAuth, OIDC, SSO, Okta, ActiveDirectory, EC2, S3, EKS, Lambda, RDS, Route53, EntraID, CI/CD, Scrum 🏢 Description: We are an AI-native data and technology partner for private capital and healthcare. Founded in 2010 and headquartered in Warsaw, we work with leading PE firms, VC funds, and healthcare organizations to build proprietary data infrastructure, deploy AI solutions, and drive AI-native transformation. Our clients manage a cumulative $210B+ in assets. Our average engagement runs five years. Our NPS sits above 80. We don't need to claim credibility — we can show it. We've also done to ourselves what we now do for clients. We've restructured our own company around AI — tools, policies, roles, delivery models. This isn't a pitch. It's a playbook we've already run, and we're hiring the engineers who will run it for others. The Project: We are carrying out the project for our client, an American private equity and investment management fund - listed on the Forbes 500 list - based in New York. We support them in the area of data pipeline, infrastructure and data engineering team. They operate very widely in the world of finance, loans, investments and real estate. Tech stack AWS (EC2, ELB, IAM, Lambda, RDS, Route53, S3, Athena, Redshift, EKS), Azure (Entra ID / Copilot integration), Terraform, Python, Bash, SQL, Docker, Kubernetes, Apache Airflow, Snowflake, GitLab, Artifactory, SQLAlchemy. Best practices: CI/CD, Code Reviews, Scrum. Your responsibilities Designing, building and maintaining cloud infrastructure across AWS environments, with Azure involvement where needed for Copilot integration Writing and owning Infrastructure-as-Code (Terraform) — from greenfield builds to ongoing refactors Running containerized workloads (Docker, Kubernetes) across multi-region setups Owning observability: logging, metrics, dashboards, reliability targets, operational runbooks Engineering identity and auth solutions — IAM policies, Entra ID, OAuth/OIDC, SSO, Okta, token ownership, service vs. user auth, cross-platform access Debugging real production issues: API failures, auth loops, rate limits, model config problems, client SDK bugs, capacity constraints Building reusable tooling and infrastructure for data scientists and engineers Supporting the broader data engineering team with DevOps expertise Documenting what you build — clearly and thoroughly What we're looking for 10+ years in IT, including 5+ years in a DevOps/Cloud role Deep AWS expertise (IAM, EC2, S3, EKS and beyond); Azure awareness for Copilot-adjacent work Solid Terraform background — you've owned IaC end-to-end, not just contributed to it Kubernetes experience: setting it up from scratch, scaling, day-2 operations Docker proficiency Strong Python and Bash skills Identity and auth engineering: IAM, Entra ID, OAuth/OIDC, SSO, Okta, Active Directory Observability and SRE mindset — you write runbooks, you own reliability, you don't just monitor Experience with relational and NoSQL databases C1+ English — written and spoken Nice to have Experience with data pipeline tools (Airflow, Snowflake, Redshift, Athena) Familiarity with Artifactory or similar repository managers Experience in secure/corporate networking environments (proxies, firewalls) Python data stack: Pandas, NumPy, SQLAlchemy; basic ML libraries a plus Comfort working in both Windows and Unix environments Benefits Unrestricted AI Stack & Premium Gear: Fully paid licenses for Cursor, Claude Pro, etc. Work with a talented team redefining the global perception of Poland Flexible working hours and remote work options Comfortable office in central Warsaw with all essential tools Multisport card & private medical care A culture of feedback – evaluation meetings, mentoring, and career growth opportunities Frontier Engineering Culture: Build alongside elite engineers who are shipping systems that drive real investment decisions. Backed by continuous growth and a strong knowledge-sharing culture ( check our YouTube ). Sounds like a perfect place for you? Don’t hesitate to click apply and submit your application today!

🏢 Summary: Lead AI Forward Deployment Engineer role focused on deploying, securing, and scaling AI solutions in enterprise environments using Google Cloud. The position bridges AI R&D and production by architecting Vertex AI pipelines, managing GKE clusters, and integrating AI into existing systems. It involves leading technical deployments and ensuring robust security for large-scale AI workloads. 🗂️ Requirements: 10+ years experience in Distributed Systems, Data Engineering, or DevOps, Expert-level knowledge of GCP and Vertex AI, Proven experience with GKE, Helm, and Istio, Strong Python experience with asynchronous and scalable backend development, Hands-on experience securing endpoints and AI systems, Experience designing end-to-end AI pipelines, Ability to manage GPU/TPU workloads, Legal work permit in Poland 📃 Skills: GCP, VertexAI, GKE, Kubernetes, Helm, Istio, Python, APIs, Microservices, DistributedSystems, DevOps, FeatureStore, Pipelines, ModelGarden, CloudArmor, ModelArmor, WAF, GPU, TPU, Networking, VPC 🏢 Description: Project info: We are seeking a skilled Lead AI Forward Deployment Engineer (GCP) to join our client's team. As a “Special Ops Engineer”, you will bridge the gap between our AI R&D and enterprise production. You will deploy, secure, and scale AI solutions within complex client environments using the Google Cloud ecosystem. Responsibilities: Production AI: Architect end-to-end pipelines on Vertex AI (Model Garden, Pipelines, and Feature Store). Security Hardening: Implement Model Armor for LLM safety (prompt injection/PII filtering) and Cloud Armor for edge-layer WAF protection. Orchestration: Design and manage high-scale Google Kubernetes Engine (GKE) clusters, optimizing for GPU/TPU workloads. Integration: Write production-grade Python microservices and APIs to embed AI into existing enterprise workflows. Client Leadership: Lead technical deployments on-site or in-client VPCs, navigating complex networking and legacy constraints. Job requirements: 10+ Years Engineering: Deep background in Distributed Systems, Data Engineering, or DevOps. GCP Mastery: Expert-level knowledge of Vertex AI and the broader GCP ecosystem. K8s Expert: Proven experience with GKE, Helm, and Service Mesh (Istio). Python Veteran: Master of asynchronous programming and scalable backend design. Security Expert: Hands-on experience securing endpoints and managing AI-specific vulnerabilities. Must possess a legal work permit in Poland Benefits: General benefits - depends on the form of employment Hybrid work model & remote work Attractively located office with collaboration spaces Onsite parking space for employees Referral program with financial bonus Life Insurance Budget for development (including language courses and others), clear career path with the possibility to gain experience in international environment Access to internal Learning Platform with multiple trainings oriented for professional growth Lifestyle benefits: Access to MyBenefit platform (Multisport included) Team Building activities Charity initiatives Working environment promoting diversity and inclusion Health benefits: Private medical care - Platinum Package

🏢 Summary: Backend engineering role focused on building and operating production-grade systems for agentic AI platforms. The position involves designing backend services, APIs, and distributed systems while collaborating across teams to deliver scalable and secure AI-driven solutions. Candidates will work with cloud infrastructure, databases, and AI tooling in a fast-paced engineering environment. 🗂️ Requirements: 3–5 years of backend engineering experience, Strong Python skills, Experience building production systems, Knowledge of distributed systems, Experience with AWS, GCP, or Azure, Experience with SQL and NoSQL databases, Understanding of schema design, Security-conscious engineering approach, Ability to deliver production-ready solutions, Clear written and verbal communication, Experience using AI tools in engineering workflows 📃 Skills: Python, AWS, GCP, Azure, SQL, NoSQL, TypeScript, AI, LLM, GitHub, Copilot, Codex 🏢 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 backend engineer with a few years of experience who wants to own real systems, not just implement tickets. You will take on meaningful backend problems, work out the right approach, ship it, and help keep it healthy in production. We want someone who is technically solid, communicates clearly, and is growing the judgment to make systems simpler, safer, and easier to evolve over time. You will own real work from design through production, with the support of a strong team around you. The hard part is real: building reliable, production-grade systems for agentic AI is a genuinely unsolved problem, and you'd work on it with real customers already depending on the result. That mix — real customers betting on us and problems the industry hasn't figured out yet, at startup speed — is rare. 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. What You Will Own Build and ship backend services, APIs, data flows, and background processing for production systems Turn requirements into concrete technical plans, trade-offs, and execution Help own services after launch: reliability, observability, performance, and incident follow-through Make sound decisions around interfaces, data models, and how your services fit the larger system Write clear technical notes and diagrams when they help the team move faster 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 Contribute to a high quality bar through code review and design review What Strong Performance Looks Like You move backend work forward with growing independence, asking for help at the right moments rather than waiting to be told what to do Your services get easier to operate and change as your design judgment grows You communicate trade-offs clearly and are a reliable teammate You use AI tools well: to accelerate analysis, implementation, debugging, writing, and repetitive work, while keeping a high verification bar What We Are Looking For Around 3 to 5 years of backend engineering experience building production systems Strong Python skills and the ability to write clean, maintainable backend code A working grasp of distributed systems: concurrency, failure handling, data consistency, async work, and service boundaries, with the appetite to deepen it Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure Comfort with SQL and NoSQL systems and a solid feel for schema design A security-conscious approach to engineering: you 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 a shipped, production-ready result with growing 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 want to keep pushing that further Strong Plus Exposure to agentic systems: AI agents, tool-calling, orchestration, retrieval, or LLM-backed infrastructure Working knowledge of TypeScript or the ability to contribute across the stack when needed A track record of growing fast and taking on more than your title strictly required 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 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: Frontend Engineer role focused on building production-ready Next.js SSR applications that power enterprise AI interfaces at scale. The position involves architecting complex state management, real-time LLM streaming experiences, and high-performance data-heavy UIs integrated with enterprise systems. You will own features end-to-end, ensuring accessibility, security, and performance for mission-critical AI-driven workflows. 🗂️ Requirements: 5+ years frontend engineering experience, 3+ years experience with React and modern JavaScript/TypeScript, Production experience with Next.js SSR applications, Advanced TypeScript expertise, Experience with complex state management in real-time or multi-tenant applications, Experience building enterprise applications with i18n, accessibility, and security standards, Experience building AI/LLM interfaces with streaming or real-time interactions, Proven ability to optimize high-load, data-heavy applications, Strong expertise in modern CSS (Tailwind CSS or CSS-in-JS), Experience with observability and monitoring tools, Experience using AI coding assistants in development, Upper-Intermediate English proficiency 📃 Skills: React, Next.js, TypeScript, JavaScript, SWR, REST, WebSockets, Tailwind, CSS, Storybook, ReactFlow, Highcharts, Playwright, Datadog, Sentry, Elasticsearch, DynamoDB, PostgreSQL, Aurora, AI, LLM 🏢 Description: As a Frontend Engineer at Shelf, you’ll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we’re solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability? You won’t just build React components — you’ll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information. This is frontend engineering at its most demanding. You’ll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts. We obsess over frontend quality because we’re building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you’re not just meeting UX standards — you’re directly enabling users to trust AI-powered answers and make critical business decisions with confidence. You’ll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features. We’re a product company that ships fast without compromising on lasting quality. You’ll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn’t just what we build — it’s how we build. The best engineers we know are drawn to problems that matter. If you’re excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn’t figured out yet. Responsibilities Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenarios and real-time AI interactions at scale Build interfaces for AI-powered features including streaming LLM responses, semantic search across millions of documents, interactive knowledge graphs, intelligent content recommendations, and AI agentic builders Architect component libraries and maintain our design system in Storybook, ensuring reusability, accessibility, and consistent UX patterns across the platform Develop enterprise-grade functionality including multi-language support, accessibility compliance, cross-browser compatibility, and security implementations that meet SOC 2 standards Create comprehensive technical specifications and component API designs that clearly communicate interface decisions, performance trade-offs, and accessibility considerations Build and optimize data-heavy UIs using React Flow for node-based graphs, Highcharts for analytics visualizations, and custom virtualization for handling large datasets Instrument components for performance monitoring, track Core Web Vitals, implement error boundaries, and build automated visual regression tests with Playwright Take full ownership of the features you build, monitoring their performance in production, optimizing bundle sizes, and ensuring they scale gracefully as user load grows Work with SWR for intelligent data fetching, caching, and revalidation strategies that minimize API calls while keeping UIs responsive and data fresh Integrate with backend services via REST APIs, handle websocket connections for real-time updates, and implement optimistic UI patterns for seamless user experiences Leverage AI coding assistants to accelerate development while maintaining high code quality, and contribute to building internal AI agents that automate frontend workflows Stay current with React ecosystem best practices, Next.js updates, AI UX patterns, and modern frontend architecture—experiment with new approaches and share findings with the team Contribute to our engineering standards and practices through thoughtful code reviews, mentor colleagues on frontend best practices, and actively participate in our culture of continuous learning Requirements Over 5 years of professional frontend engineering experience, including more than 3 years specializing in React and modern JavaScript/TypeScript Production Next.js experience — you’ve built and shipped SSR applications at scale, understand app router patterns, server components, and the trade-offs between SSR, SSG, and CSR Deep TypeScript expertise — you write type-safe code with generics, utility types, and advanced patterns. Complex state management — hands-on experience architecting state solutions for challenging scenarios: real-time collaboration, optimistic updates, multi-tenant data isolation, and large-scale data synchronization Enterprise application development — you’ve built applications with localization (i18n), accessibility, security best practices, and compliance requirements. You understand the complexity beyond “making it work” AI/LLM interface experience — you’ve built interfaces for AI-powered features: streaming token responses, chat UIs, semantic search, or similar real-time AI interactions High-load optimization — proven track record optimizing applications for performance under heavy traffic, large datasets, and concurrent operations. You monitor Core Web Vitals and know how to improve them Modern CSS mastery — strong expertise with Tailwind CSS and/or CSS-in-JS solutions. You can implement pixel-perfect designs while maintaining responsive layouts and dark mode support Write well-structured, testable code with thoughtful component abstractions and clean APIs. You know when to abstract and when to keep it simple Strong problem-solving skills and genuine curiosity — you don’t wait for designs to be perfect but proactively identify UX issues and propose solutions. You’re never satisfied with “good enough” and constantly refine your craft Experience with AI coding assistants (OpenAI Codex, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the frontend workflow Familiarity with observability and monitoring tools like Datadog, Sentry, or similar platforms for tracking frontend performance and errors in production Upper-Intermediate or better English skills for technical communication, documentation, and collaborating with distributed teams Present your work effectively both verbally and visually — you can articulate design decisions, create component documentation, and explain technical trade-offs clearly Be a Plus: Experience with React Flow, Highcharts, or other complex data visualization libraries Understanding of Node.js/Python/backend fundamentals — you can read backend code and contribute to API design discussions Experience with SWR, React Query, or similar data fetching libraries Hands-on experience with vector search UIs, RAG interfaces, or semantic search implementations Familiarity with MCP (Model Context Protocol), DSPy, or other cutting-edge AI frameworks Experience with monorepo tools (Lerna, Turborepo, Nx) and managing shared component libraries AWS services knowledge (S3, CloudFront, Lambda) and understanding of serverless architectures Built or contributed to design systems or open-source component libraries Experience with Playwright, Puppeteer, or Cypress for comprehensive E2E testing Experience building AI agent interfaces or agentic AI workflows What Shelf Offers: B2B contract Company Stock Options Hardware: MacBook Pro Modern technical stack. Develop open-source software Premier AI development environment: GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, v0, MCP Servers, plus credits for experimenting with emerging AI tools Why Shelf GenAI will be at least a $18 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale We are blazing the path for the future of Artificial Intelligence globally. Our Leadership Team has deep AI domain expertise and enterprise SaaS background to execute this plan We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all — it’s the improvements they see in their business KPIs. We have raised over $60 million in funding and our investors include; Insight Partners, Tiger Global, Base10, and others We have high velocity growth powered by the most innovative product in our category We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few quarters.

🏢 Summary: Frontend Engineer role focused on building production-grade Next.js SSR applications that power enterprise AI interfaces with real-time LLM streaming, complex state management, and high-load performance. The position involves architecting scalable, accessible, and secure UIs integrated with AI systems and large-scale data services. It requires delivering performant, enterprise-ready frontend solutions for mission-critical AI-driven workflows. 🗂️ Requirements: 5+ years frontend engineering experience, 3+ years commercial experience with React, Production experience with Next.js SSR applications, Advanced TypeScript expertise, Experience with complex state management in large-scale applications, Experience building AI/LLM interfaces with real-time streaming, Proven performance optimization for high-load applications, Experience with enterprise features: i18n, accessibility, security compliance, Strong knowledge of modern CSS and responsive design, Experience integrating REST APIs and WebSockets, Experience with observability and frontend monitoring tools, Experience with AI coding assistants 📃 Skills: React, Next.js, TypeScript, JavaScript, SWR, REST, WebSockets, Tailwind, CSS, Storybook, ReactFlow, Highcharts, Playwright, Datadog, Sentry, Elasticsearch, DynamoDB, PostgreSQL, Aurora, SOC2 🏢 Description: As a Frontend Engineer at Shelf, you’ll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we’re solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability? You won’t just build React components — you’ll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information. This is frontend engineering at its most demanding. You’ll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts. We obsess over frontend quality because we’re building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you’re not just meeting UX standards — you’re directly enabling users to trust AI-powered answers and make critical business decisions with confidence. You’ll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features. We’re a product company that ships fast without compromising on lasting quality. You’ll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn’t just what we build — it’s how we build. The best engineers we know are drawn to problems that matter. If you’re excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn’t figured out yet. Responsibilities Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenarios and real-time AI interactions at scale Build interfaces for AI-powered features including streaming LLM responses, semantic search across millions of documents, interactive knowledge graphs, intelligent content recommendations, and AI agentic builders Architect component libraries and maintain our design system in Storybook, ensuring reusability, accessibility, and consistent UX patterns across the platform Develop enterprise-grade functionality including multi-language support, accessibility compliance, cross-browser compatibility, and security implementations that meet SOC 2 standards Create comprehensive technical specifications and component API designs that clearly communicate interface decisions, performance trade-offs, and accessibility considerations Build and optimize data-heavy UIs using React Flow for node-based graphs, Highcharts for analytics visualizations, and custom virtualization for handling large datasets Instrument components for performance monitoring, track Core Web Vitals, implement error boundaries, and build automated visual regression tests with Playwright Take full ownership of the features you build, monitoring their performance in production, optimizing bundle sizes, and ensuring they scale gracefully as user load grows Work with SWR for intelligent data fetching, caching, and revalidation strategies that minimize API calls while keeping UIs responsive and data fresh Integrate with backend services via REST APIs, handle websocket connections for real-time updates, and implement optimistic UI patterns for seamless user experiences Leverage AI coding assistants to accelerate development while maintaining high code quality, and contribute to building internal AI agents that automate frontend workflows Stay current with React ecosystem best practices, Next.js updates, AI UX patterns, and modern frontend architecture—experiment with new approaches and share findings with the team Contribute to our engineering standards and practices through thoughtful code reviews, mentor colleagues on frontend best practices, and actively participate in our culture of continuous learning Requirements Over 5 years of professional frontend engineering experience, including more than 3 years specializing in React and modern JavaScript/TypeScript Production Next.js experience — you’ve built and shipped SSR applications at scale, understand app router patterns, server components, and the trade-offs between SSR, SSG, and CSR Deep TypeScript expertise — you write type-safe code with generics, utility types, and advanced patterns. Complex state management — hands-on experience architecting state solutions for challenging scenarios: real-time collaboration, optimistic updates, multi-tenant data isolation, and large-scale data synchronization Enterprise application development — you’ve built applications with localization (i18n), accessibility, security best practices, and compliance requirements. You understand the complexity beyond “making it work” AI/LLM interface experience — you’ve built interfaces for AI-powered features: streaming token responses, chat UIs, semantic search, or similar real-time AI interactions High-load optimization — proven track record optimizing applications for performance under heavy traffic, large datasets, and concurrent operations. You monitor Core Web Vitals and know how to improve them Modern CSS mastery — strong expertise with Tailwind CSS and/or CSS-in-JS solutions. You can implement pixel-perfect designs while maintaining responsive layouts and dark mode support Write well-structured, testable code with thoughtful component abstractions and clean APIs. You know when to abstract and when to keep it simple Strong problem-solving skills and genuine curiosity — you don’t wait for designs to be perfect but proactively identify UX issues and propose solutions. You’re never satisfied with “good enough” and constantly refine your craft Experience with AI coding assistants (OpenAI Codex, Claude, etc.) and eagerness to push the boundaries of AI-assisted development. Part of this role involves creating AI agents to automate portions of the frontend workflow Familiarity with observability and monitoring tools like Datadog, Sentry, or similar platforms for tracking frontend performance and errors in production Upper-Intermediate or better English skills for technical communication, documentation, and collaborating with distributed teams Present your work effectively both verbally and visually — you can articulate design decisions, create component documentation, and explain technical trade-offs clearly Be a Plus: Experience with React Flow, Highcharts, or other complex data visualization libraries Understanding of Node.js/Python/backend fundamentals — you can read backend code and contribute to API design discussions Experience with SWR, React Query, or similar data fetching libraries Hands-on experience with vector search UIs, RAG interfaces, or semantic search implementations Familiarity with MCP (Model Context Protocol), DSPy, or other cutting-edge AI frameworks Experience with monorepo tools (Lerna, Turborepo, Nx) and managing shared component libraries AWS services knowledge (S3, CloudFront, Lambda) and understanding of serverless architectures Built or contributed to design systems or open-source component libraries Experience with Playwright, Puppeteer, or Cypress for comprehensive E2E testing Experience building AI agent interfaces or agentic AI workflows What Shelf Offers: B2B contract Company Stock Options Hardware: MacBook Pro Modern technical stack. Develop open-source software Premier AI development environment: GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, v0, MCP Servers, plus credits for experimenting with emerging AI tools Why Shelf GenAI will be at least a $18 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale We are blazing the path for the future of Artificial Intelligence globally. Our Leadership Team has deep AI domain expertise and enterprise SaaS background to execute this plan We love our customers and our customers love us. Ask a Shelf customer why, and they’ll tell you it’s because of our innovative capabilities, rock-solid reliability, they truly enjoy working with our people, but most of all — it’s the improvements they see in their business KPIs. We have raised over $60 million in funding and our investors include; Insight Partners, Tiger Global, Base10, and others We have high velocity growth powered by the most innovative product in our category We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few quarters.

🏢 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