Senior Full Stack Product Engineer

🏢 Summary: Senior Backend Engineer role focused on owning and designing production-grade backend systems, from ambiguous problem definition through architecture, implementation, and long-term reliability. The position emphasizes strong system design, distributed systems judgment, and hands-on cloud engineering, with full ownership of services in production. This is a product engineering role with end-to-end responsibility across backend architecture, scalability, and operational excellence. 🗂️ Requirements: Senior-level backend engineering experience in production systems, Strong Python proficiency, Experience designing and operating distributed systems, Knowledge of concurrency, failure handling, and data consistency, Hands-on cloud experience (AWS, Azure or similar), Experience with SQL and NoSQL databases, Ability to design data models and perform schema design, Experience with performance tuning and scalability, Ability to design, implement, and operate backend services end-to-end, Experience using AI tools in daily engineering workflow 📃 Skills: Python, AWS, Azure, SQL, NoSQL, Concurrency, DistributedSystems, Async, APIs, Microservices, LLM, TypeScript 🏢 Description: About Shelf Shelf builds software that helps enterprises make AI work in the real world. We care about the hard part: reliable systems, clear operational logic, and production-grade engineering that makes AI useful instead of brittle. Job Description: This role is for a senior backend engineer who can own important systems, not just implement tickets. You will take ambiguous problems, design the right backend approach, ship it, and keep it healthy in production. We want someone who is strong technically, communicates clearly, and has the judgment to make systems simpler, safer, and easier to evolve over time. This is a product engineering role with real ownership from system design through production. Location – Warsaw, work from the office What You Will Own Design and ship backend services, APIs, data flows, and background processing for production systems. Turn vague requirements into concrete technical plans, trade-offs, and execution. Own services after launch: reliability, observability, performance, and incident follow-through. Make sound decisions around system boundaries, data models, interfaces, and scaling paths. Write clear technical specs, architecture 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. Raise the quality bar through code review, design review, and pragmatic technical leadership. What Strong Performance Looks Like You reliably move important backend work forward without waiting to be tightly managed. Your systems are easier to operate and easier to change because of your design decisions. You communicate trade-offs clearly and make the team around you more effective. 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 Strong senior-level backend engineering experience in production systems. Strong Python skills and the ability to design clean, maintainable backend code. Good distributed systems judgment: concurrency, failure handling, data consistency, async work, and service boundaries. Hands-on cloud experience in AWS, Azure, or a similar environment. Comfort with SQL and NoSQL systems, schema design, and performance tuning. Ability to go from problem statement to design to production rollout with real ownership. Clear written and verbal communication. You can explain systems, trade-offs, and incidents without hiding behind jargon. AI-native working style. You already use AI tools in your daily engineering workflow and want to keep pushing that further. Strong Plus Experience with LLM-backed systems, search, retrieval, AI infrastructure, or data-heavy pipelines. Working knowledge of TypeScript or the ability to contribute across the stack when needed. Experience shaping technical direction for other engineers, even without formal management responsibility. How We Evaluate Fit We care more about ownership, systems judgment, and learning velocity than a perfect keyword match to our stack. If you are the kind of engineer who can take a messy problem and turn it into a strong production system, we want to talk. What Shelf Offers: B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. Access to Claude Code, OpenAI Codex, TypingMind, and MCP Servers. Why Shelf: Our Leadership Team has deep knowledge management and 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 Tiger Global, Insight Partners, Connecticut Innovations, and others We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

🏢 Summary: Senior Backend Engineer role focused on designing, shipping, and owning production-grade backend systems for enterprise AI software. The position requires turning ambiguous problems into scalable architectures and maintaining reliability, performance, and observability in production. It is a product engineering role with full ownership from system design to rollout. 🗂️ Requirements: Senior-level backend engineering experience in production systems, Strong Python proficiency, Experience designing distributed systems, Knowledge of concurrency and async processing, Experience with failure handling and data consistency, Hands-on cloud experience (AWS or Azure), Experience with SQL and NoSQL databases, Ability to design data models and system boundaries, Experience building and maintaining APIs and backend services, Production experience with observability and performance tuning, Ability to write technical specifications and architecture documentation, Experience using AI tools in engineering workflows 📃 Skills: Python, AWS, Azure, SQL, NoSQL, APIs, DistributedSystems, Concurrency, Async, Observability, LLM, TypeScript 🏢 Description: About Shelf Shelf builds software that helps enterprises make AI work in the real world. We care about the hard part: reliable systems, clear operational logic, and production-grade engineering that makes AI useful instead of brittle. Job Description: This role is for a senior backend engineer who can own important systems, not just implement tickets. You will take ambiguous problems, design the right backend approach, ship it, and keep it healthy in production. We want someone who is strong technically, communicates clearly, and has the judgment to make systems simpler, safer, and easier to evolve over time. This is a product engineering role with real ownership from system design through production. Location – Warsaw, work from the office What You Will Own Design and ship backend services, APIs, data flows, and background processing for production systems. Turn vague requirements into concrete technical plans, trade-offs, and execution. Own services after launch: reliability, observability, performance, and incident follow-through. Make sound decisions around system boundaries, data models, interfaces, and scaling paths. Write clear technical specs, architecture 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. Raise the quality bar through code review, design review, and pragmatic technical leadership. What Strong Performance Looks Like You reliably move important backend work forward without waiting to be tightly managed. Your systems are easier to operate and easier to change because of your design decisions. You communicate trade-offs clearly and make the team around you more effective. 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 Strong senior-level backend engineering experience in production systems. Strong Python skills and the ability to design clean, maintainable backend code. Good distributed systems judgment: concurrency, failure handling, data consistency, async work, and service boundaries. Hands-on cloud experience in AWS, Azure, or a similar environment. Comfort with SQL and NoSQL systems, schema design, and performance tuning. Ability to go from problem statement to design to production rollout with real ownership. Clear written and verbal communication. You can explain systems, trade-offs, and incidents without hiding behind jargon. AI-native working style. You already use AI tools in your daily engineering workflow and want to keep pushing that further. Strong Plus Experience with LLM-backed systems, search, retrieval, AI infrastructure, or data-heavy pipelines. Working knowledge of TypeScript or the ability to contribute across the stack when needed. Experience shaping technical direction for other engineers, even without formal management responsibility. How We Evaluate Fit We care more about ownership, systems judgment, and learning velocity than a perfect keyword match to our stack. If you are the kind of engineer who can take a messy problem and turn it into a strong production system, we want to talk. What Shelf Offers: B2B contract. Company Stock Options. Hardware: MacBook Pro. Modern technical stack . Develop open-source software . GitHub Copilot subscription. Access to Claude Code, OpenAI Codex, TypingMind, and MCP Servers. Why Shelf: Our Leadership Team has deep knowledge management and 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 Tiger Global, Insight Partners, Connecticut Innovations, and others We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

🏢 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: Senior DevOps / Platform Engineer role focused on owning deployment, reliability, and operational excellence for a Voice AI product in production. The position emphasizes hands-on infrastructure, CI/CD, observability, and running AI-heavy voice systems at scale. The engineer will independently improve production systems, developer workflows, and operational standards. 🗂️ Requirements: Senior-level experience in DevOps, Platform Engineering, SRE, or Infrastructure Engineering, Strong cloud experience with AWS, Azure, or similar, Hands-on experience with Infrastructure as Code, Experience building and maintaining CI/CD pipelines, Strong knowledge of reliability, observability, and incident response practices, Experience operating production systems, Ability to work across infrastructure and backend layers, Experience using AI tools in daily engineering workflows, On-site work in Warsaw 📃 Skills: AWS, Azure, CI/CD, IaC, SRE, DevOps, STT, TTS, STS, Observability, Infrastructure, Cloud, AI 🏢 Description: About Shelf Shelf builds software that helps enterprises make AI work in the real world. For our Voice AI product, that means reliable runtime systems, strong deployment paths, and production infrastructure that lets engineering teams move fast without creating operational chaos. About the role This role is for a senior DevOps / platform engineer who can independently own how our Voice AI product ships and runs. You will work directly with the team building our Voice AI product rather than as part of a generic centralized Platform function. The job is to make deployment, reliability, observability, and operational quality materially better. That includes infrastructure, CI/CD, environments, incident follow-through, and the practical realities of running AI-heavy systems in production. Real hands-on experience deploying voice-related systems such as STT, TTS, or STS workloads is a strong plus because it is highly relevant to the direction of the work. Location – Warsaw, work from the office What You Will Own Improve how Voice AI services are deployed, run, observed, and supported in production. Build and maintain infrastructure as code, CI/CD flows, environment setup, and paved paths that reduce developer friction. Strengthen observability with better logs, metrics, traces, dashboards, and alerts. Improve reliability through better operational standards, incident handling, post-incident follow-through, and practical SLO thinking. Work across application and infrastructure boundaries when that is what the problem requires. Reduce recurring toil through automation, documentation, and better defaults. Make sound trade-offs around cost, security, performance, and speed. Use AI tools aggressively and well to increase your own leverage and improve engineering workflows. What Strong Performance Looks Like The Voice AI team can ship faster and with fewer avoidable operational issues because of your work. The systems you touch become easier to understand, easier to operate, and easier to trust. You do not need heavy management to create momentum; you find important gaps and close them. You handle real production problems without drama and improve the system after the immediate issue is over. What We Are Looking For Strong senior-level experience in platform engineering, DevOps, SRE, infrastructure engineering, or a similar hands-on role. Strong cloud and infrastructure fundamentals in AWS, Azure, or a comparable environment. Real experience with infrastructure as code and modern delivery pipelines. Strong operational judgment around reliability, observability, incident response, and production systems. Comfort moving across layers: infrastructure, backend services, developer workflows, and operational tooling. Clear communication and strong written habits, especially around runbooks, postmortems, and technical decision making. AI-native working style. You already use AI tools in daily engineering work and think in terms of leverage, automation, and better workflows. Strong Plus Real hands-on experience deploying or operating STT, TTS, STS, or similar voice-model workloads. Experience improving developer experience for product teams, not just operating infrastructure in isolation. Experience with security, access control, compliance-minded infrastructure, and pragmatic operational guardrails. Ability to debug problems that cut across application code, infrastructure, and third-party systems. How We Evaluate Fit We care more about independent ownership, systems judgment, and practical operating ability than about a perfect keyword match to every tool we use. If you are the kind of engineer who can step into a messy production environment and make it calmer, faster, and more reliable, we want to talk. 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, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools Why Shelf: GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan We've been helping our customers prevent knowledge mismanagement since our founding in 2017 We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months

🏢 Summary: Senior / Staff Full Stack Engineer role focused on building and scaling an AI-driven product platform in a fully remote setup. The position involves developing React/TypeScript frontend experiences and Python-based backend APIs to support document processing, retrieval systems, and structured AI/ML outputs. The engineer will integrate frontend, backend, and AI workflows into a reliable, testable product experience. 🗂️ Requirements: 5+ years full stack engineering experience, Strong Python backend API development experience, Strong React and TypeScript production experience, Experience with modern API frameworks (e.g. FastAPI), Experience designing and consuming API contracts and structured JSON, Experience with asynchronous workflows and background jobs, Testing experience covering edge cases and API behavior, Understanding of AI/ML product workflows 📃 Skills: Python, React, TypeScript, FastAPI, API, JSON, AI, ML, LLM, OpenAI, Gemini, Anthropic, Embeddings, Vector, Firebase, Firestore, GCP, CloudRun, CloudSQL, Neo4j 🏢 Description: We are looking for a Senior / Staff Full Stack Engineer with strong Python and React experience to build and scale an AI driven product platform in a fully remote setup. The role focuses on frontend experiences, backend APIs, document processing, retrieval systems, and structured AI / ML outputs. ✅ Your responsibilities: Building frontend experiences in React and TypeScript for evidence review, workflow status, recommendations, and decision outputs. Developing backend APIs in Python, ideally with FastAPI, for document upload, asynchronous processing, job status, retries, partial success, and structured results. Connecting frontend, backend, data workflows, retrieval systems, and AI generated outputs into a reliable product experience. Building product features that make AI outputs easier to inspect through source references, confidence signals, warnings, and clear error states. Working with structured data, documents, tables, financial metrics, and normalized evidence flows. Writing tests around API contracts, edge cases, error cases, and realistic user workflows. 🧠 Our requirements: 5+ years of professional full stack engineering experience. Strong experience with Python and backend API development. Strong experience with React and TypeScript in production applications. Experience with modern API frameworks, ideally FastAPI or similar. Understanding of AI / ML product workflows or strong interest in building software around AI outputs. Experience designing and consuming API contracts, schemas, and structured JSON payloads. Comfort with asynchronous workflows, background jobs, retries, partial failures, and user visible process status. Good testing habits, especially around edge cases, failure cases, and API behavior. ⭐ Nice to Have: Experience with AI / ML product workflows, including retrieval systems, embeddings, vector search, LLM based applications, or LLM APIs such as OpenAI, Gemini, Anthropic/Claude. Experience with data heavy products, including data workflows, document processing, data normalization, or working with structured evidence. Experience with cloud and data infrastructure, ideally Firebase, Firestore, Google Cloud Platform, Cloud Run, Cloud SQL, vector search, or Neo4j. 🌟 What we offer: 100% remote work Opportunity to work on modern ML/AI infrastructure Private healthcare and Multisport Life insurance Real influence on technical decisions and architecture Exposure to cutting-edge technologies Collaborative and supportive team environment

🏢 Summary: Senior Fullstack Engineer role focused on delivering full-stack solutions within an AI-integrated SDLC where AI is embedded across planning, development, review, testing, and deployment. The position combines backend and frontend engineering with AI orchestration, automation, and cloud-native architecture in a remote-first setup. The engineer will also evolve shared AI toolchains and contribute to architectural and code quality standards. 🗂️ Requirements: Team-level AI-integrated SDLC experience across planning, development, review, testing, deployment, Shared AI toolchain management under version control, Hands-on use of Claude Code, GitHub Copilot, Cursor or equivalent as team tools, Building and maintaining custom AI skills and sub-agents for team use, Experience with parallel AI agent orchestration, Spec-driven development using OpenAPI, ADRs, PRDs as AI context, AI-assisted code review integrated into PR process, Working knowledge of AI orchestration frameworks, Backend development with .NET / C# and ASP.NET Core, Frontend development with TypeScript and React or Angular, Experience with SQL databases and ORM frameworks, Experience with Docker and Kubernetes, Experience with CI/CD pipelines, Experience with cloud platforms (Azure, AWS, or GCP) 📃 Skills: C#, .NET, ASP.NET, SQL, SQLServer, PostgreSQL, EFCore, OAuth, JWT, Python, Java, Node.js, TypeScript, JavaScript, React, Angular, LangChain, LlamaIndex, CrewAI, Docker, Kubernetes, GitHubActions, AzureDevOps, Azure, AWS, GCP, OpenAPI, CQRS, DDD, EventSourcing, Microservices 🏢 Description: We are looking for a Senior Fullstack Engineer who combines deep technical expertise with real, team-level experience working in an AI-integrated software development lifecycle. Individual use of AI coding assistants is not sufficient for this role. We are specifically looking for engineers who have worked in teams where AI was embedded into every phase of delivery — from planning and design through development, review, testing, and deployment. We follow a remote-first setup with no mandatory regular office visits for this position. From time to time, you may be invited to join in-person meetings in one of our offices (Warsaw, Lodz, Wroclaw, Gdansk, or Bialystok), for example for client visits or team reunions. AI-First Requirements Experience working in an AI-enabled engineering team is mandatory — not a personal workflow preference. You have been part of a team where AI was systematically embedded across all delivery phases: planning, development, review, testing, and deployment. You can speak from direct experience about how it worked, what failed, and what you would change. Specific mandatory requirements: Team-level AI-integrated SDLC experience — shared toolchain, shared configurations, shared assets under version control Hands-on with Claude Code, GitHub Copilot, Cursor, or equivalent as a team tool, not only personal usage Built and maintained custom skills and sub-agents used across a team, not just personally Experience with parallel agent orchestration for concurrent workstream execution Disciplined plan → review plan → execute approach with AI involved at every phase Maintained shared prompt libraries, skill repositories, or agent configurations in version control AI-assisted code review integrated into the PR process: CodeRabbit, Copilot review, or similar Experience with spec-driven or document-driven development where structured specifications (OpenAPI, ADRs, PRDs) serve as AI context inputs, not just human references Working knowledge of at least one AI orchestration framework: LangChain, LlamaIndex, Microsoft Agent Framework, CrewAI, or equivalent Automation-first mindset: proactively identify repetitive or inefficient parts of current work and automate them using AI and other available tools. Cost-aware AI usage: understanding how AI credits are consumed across different tools, models, and workflows, and ability to choose the most appropriate model or approach for each task. Technical Requirements Backend: .NET / C#, ASP.NET Core, SQL Server / PostgreSQL, EF Core, OAuth 2.0 / JWT. Python, Java, or Node.js is a strong plus. Frontend: TypeScript, JavaScript, React(preferable) and/or Angular, state management, async patterns, frontend testing. Architecture: Full spectrum from monolith to microservices — DDD, CQRS, Event Sourcing, event-driven design, message brokers. Infrastructure: Docker, Kubernetes, CI/CD (GitHub Actions / Azure DevOps), Azure / AWS / GCP, structured observability. Responsibilities Deliver full-stack features to a high standard of quality, performance, and reliability Contribute to architectural decisions and system design trade-offs Evolve and maintain the team's shared AI toolchain across all SDLC phases Conduct code reviews including AI-assisted tooling; uphold and enforce engineering best practices Proactively surface risks, bottlenecks, and security concerns Communicate and collaborate directly with clients in English Mentor engineers on both technical fundamentals and AI-augmented workflow practices Professional Qualities Ownership mindset · Strong written and verbal English · Comfortable in client-facing roles · Raises the AI workflow maturity of those around them

🏢 Summary: Senior Full Stack Developer role focused on owning and scaling a customer-facing dashboard and its underlying systems. The position covers end-to-end development across React frontend and Node.js backend, with responsibility for architecture, APIs, databases, and security. It also emphasizes AI-assisted development and driving high-quality, rapid code delivery. 🗂️ Requirements: Senior-level full stack development experience, Strong React frontend development experience, Strong Node.js backend development experience, Experience building RESTful APIs, Experience building GraphQL APIs, Experience with SQL databases, Experience with NoSQL databases, Experience with authentication and authorization implementation, Experience designing secure applications, Experience with AI-assisted development tools 📃 Skills: React, Node.js, REST, GraphQL, SQL, NoSQL, APIs, Authentication, Authorization, Security, Claude, Codex 🏢 Description: We are seeking a Senior Full Stack Developer who thrives in fast-paced environments and takes full ownership of product experiences. This role is central to building and scaling our customer-facing dashboard and the systems behind it, while driving a culture of rapid, high-quality code delivery powered by modern AI tools. Own end-to-end development of the customer-facing dashboard, including both frontend (React) and backend services Design, build, and maintain scalable full-stack applications using modern best practices Lead frontend development with React, delivering production-ready, high-performance interfaces Architect and implement backend systems using Node.js Develop and maintain APIs using both RESTful and GraphQL approaches Design and manage data models across SQL and NoSQL databases Take full responsibility for application security, including best practices in authentication, authorization, and data protection Build and evolve AI-assisted development workflows (e.g., Claude, Codex) to enable faster, more efficient code shipping Drive and instill a culture of rapid, high-quality delivery across the team, including mentoring current and new hires Collaborate with cross-functional teams to define, design, and ship new features

🏢 Summary: Senior Software Engineer role focused on designing and delivering new features and PoCs end-to-end on a large-scale SaaS and data platform. The position emphasizes backend development in Python, extending a mature system, and leveraging AI/LLM tools to accelerate development and improve engineering workflows. Fully remote with high ownership and impact on product direction. 🗂️ Requirements: 7+ years of Software Engineering experience, Strong experience with Python, Experience with Django, Experience building large-scale production systems, Experience designing and maintaining REST APIs, Strong understanding of distributed systems, Strong understanding of backend architecture, Daily practical use of AI tools and LLMs in development workflows, Experience with cloud environments, Ability to independently design and deliver end-to-end solutions, Professional English proficiency 📃 Skills: Python, Django, REST, API, SaaS, LLM, AI, Cloud, DistributedSystems, Backend 🏢 Description: Does building awesome, innovative products that add up to something meaningful sound like a dream come true? Come join us and make that vision a reality! About We are looking for a product-driven Senior Software Engineer who thrives in fast-paced environments and enjoys turning ideas into practical, user-focused solutions. In this role, you will independently design and deliver new features and PoC end-to-end on top of an existing large-scale SaaS and data platform. Rather than working in a purely greenfield environment, you will extend and evolve a mature platform with new capabilities, focusing on speed, usability, and real customer value. A key part of this role is the daily use of AI and LLM-based tools to accelerate development workflows, prototyping, research, testing, and delivery. We are looking for someone who not only uses AI tools effectively but also understands how to integrate AI reasoning and automation into modern software engineering practices. Responsibilities Independently design, prototype, and deliver new features and PoCs end-to-end Translate product ideas into scalable and user-focused backend solutions Validate technical feasibility and make pragmatic architectural decisions Use AI tools, coding copilots, and LLM-based workflows to accelerate development, experimentation, and delivery Build and maintain scalable backend services and REST APIs using Python (preferably Django) Collaborate closely with Product, Design, and Engineering teams to shape and refine new features Contribute to engineering quality through code reviews, technical guidance, and knowledge sharing Continuously explore and introduce practical AI-driven workflows that improve engineering productivity and delivery speed Our offer Competitive salary on B2B contract Fully remote position Real impact and independence at work Individual career path Work-life balance A non-corporate atmosphere where innovation, personal growth, and teamwork thrive 100+ smart, curious & ambitious engineers What you bring 7+ years of experience as a Software Engineer Strong experience with Python and preferably Django Experience building and maintaining large-scale production systems and REST APIs Strong understanding of distributed systems and modern backend architecture Demonstrated daily use of AI tools and LLMs in real engineering workflows (e.g. code generation, prototyping, refactoring, testing, documentation, automation) Experience integrating with complex platforms and cloud environments Ability to independently deliver solutions with minimal supervision Strong product mindset and focus on solving real user problems Excellent communication and collaboration skills across Product, Design, and Engineering teams Curiosity, ownership, and passion for learning and experimenting with new technologies Professional level of English Nice to Have Experience mentoring or coaching engineers Experience working with data products and related scalability challenges Experience promoting AI-driven engineering practices and helping teams adopt modern AI workflows Benefits International Projects Small Teams Flat Structure Friendly Atmosphere Flexible Hours Individual Career Path We want your TALENT! Don’t hesitate and APPLY! We are happy to tell you more details about this position in a phone call. Our recruitment process is very fast and straightforward to ensure a great experience from the first interview to joining your dream team!

🏢 Summary: Senior fullstack (backend-heavy) engineer to build a greenfield prenatal screening diagnostics product, owning architecture and features end-to-end from backend to selected frontend components. The role focuses on designing scalable Java/Spring Boot services, APIs, and data models, while contributing to React/TypeScript UI and shaping technical direction in a fast-moving MVP phase. Strong emphasis on clean architecture, testing discipline, AWS deployment, PostgreSQL, and effective use of AI-assisted development tools. 🗂️ Requirements: Strong expertise in Java and Spring Boot, Clean API design and domain modeling, Experience defining service boundaries and scalable architectures, Solid understanding of OOP, SOLID, and clean architecture, Working proficiency in React and TypeScript, Proven use of AI coding tools in daily workflow, Experience writing unit, integration, and API tests, PostgreSQL schema design and query optimization, AWS production deployment experience (ECS/EKS, RDS, Lambda, S3), Ability to work in greenfield, ambiguous environments 📃 Skills: Java, Spring, SpringBoot, React, TypeScript, PostgreSQL, AWS, ECS, EKS, RDS, Lambda, S3, REST, OOP, SOLID, SQL, AI, Cursor, Claude 🏢 Description: We are building a new prenatal screening diagnostics product from scratch. The project is currently in an early greenfield phase, with MVP delivery planned within the next six months. We are looking for a senior engineer who enjoys building products end-to-end and feels comfortable taking ownership across the full development lifecycle — from backend architecture and data modeling to APIs and selected frontend features. This role is backend-heavy, but requires a pragmatic fullstack mindset and the ability to contribute wherever needed. You will work closely with product stakeholders in a fast-moving environment, helping shape both technical direction and product decisions. We are particularly interested in engineers who actively use AI-assisted development tools (such as Cursor, Claude Code, or similar) as part of their daily workflow and understand how to leverage them effectively while maintaining high engineering standards and code quality. You will have a direct impact on: defining system architecture and service boundaries, designing scalable backend solutions, building APIs and core business logic, contributing to React/TypeScript frontend development, establishing engineering best practices, testing strategy, and maintainable code standards. The project operates in the diagnostics domain, so attention to quality, reliability, and clean engineering practices is essential. Requirements: Strong Java and Spring Boot expertise — clean API design, domain modeling, sound architectural trade-offs. You think in terms of service boundaries, data flow, and maintainability, not just making it work Solid grasp of software design principles — object-oriented programming, SOLID, clean architecture, separation of concerns. You write code that the next person can read, extend, and trust. You know when a pattern helps and when it's ceremony Working proficiency in React and TypeScript — you can pick up frontend tasks, build components, and integrate with backend APIs independently Proven experience integrating AI coding tools (Claude Code, Cursor, or equivalent) into daily development workflow — including prompt design for code generation, output validation, and actively preventing AI-generated technical debt. You can describe concrete examples of where AI accelerated your delivery and where you chose to override it Testing as a professional discipline, not a checkbox — you write unit, integration, and API tests as part of delivery, own the test pyramid decisions, and treat untested code as unfinished code PostgreSQL — schema design, query optimization, migrations in a production context AWS experience — you've deployed and operated production workloads on AWS (ECS/EKS, RDS, Lambda, S3) and can make informed infrastructure decisions Comfort working in ambiguous, greenfield settings — you define scope with stakeholders rather than waiting for pre-scoped tickets Responsibilities: Own features end-to-end: design, implement, test, deploy, and maintain across the full stack. Work split ~80% backend, 20% frontend. Make foundational architectural decisions on a greenfield codebase — data models, API contracts, service boundaries, test strategy Build and maintain the Java/Spring Boot backend that powers the product's core logic Contribute to the React/TypeScript frontend when needed — you're backend-primary, but you ship UI when the team needs it Integrate AI coding tools into your daily workflow to accelerate delivery while maintaining code quality — and help the team adopt these practices Collaborate directly with product stakeholders to refine requirements in a fast-moving, low-ceremony environment