Forward Deployed Engineer - GTM

🏢 Summary: Lead a hands-on full-stack/backend engineering effort to build scalable services, APIs, workflow engines, and agentic AI systems for logistics optimization. The role combines technical leadership, production reliability, third-party integrations, and mentoring while delivering AI-driven planning and optimization capabilities. 🗂️ Requirements: Senior or technical-lead backend engineering experience, Strong Python and API-development proficiency, Scalable distributed-systems architecture experience, API design, data modeling, and integration expertise, Agentic AI, LLM orchestration, RAG, or multi-agent systems experience, Cloud-platform and CI/CD experience, Third-party API integration experience, Production debugging experience with LLM-driven systems, Engineering mentorship and code/design review experience, Technical leadership and stakeholder communication skills, Successful pre-employment screening 📃 Skills: Python, FastAPI, TypeScript, LangGraph, LangChain, RAG, AWS, Bedrock, GitLab, CICD, SSE, WebSockets, LLM 🏢 Description: What's the role? We are looking for a Tech Lead Fullstack Engineer to build core backend systems powering next-generation agentic AI solutions for the logistics industry. The systems developed by this team optimize deliveries at scale improving driver efficiency, increasing reliability, reducing operational costs, and lowering environmental impact. In this role, you will focus on building the core service layer, customer-facing APIs, workflow engines, and integrations with HERE APIs and third-party systems that enable intelligent logistics workflows. You will work closely with senior engineers and technical leaders to design and implement scalable, reliable systems that support AI-driven planning and optimization use cases. This is a hands-on engineering role with a strong focus on backend development, system reliability, and production-quality delivery . What You’ll Do: Lead the design, build, and maintenance of core backend services, APIs, and workflow orchestration systems for logistics applications Drive integrations with HERE APIs and external third-party systems to support real-world logistics workflows Translate ambiguous product and technical requirements into scalable, maintainable system components, and help others on the team do the same Write clean, efficient, and well-tested code in Python and/or TypeScript, setting the standard for code quality across the team Design and build agentic AI systems based on LangGraph, and help shape how the team approaches LLM orchestration and multi-agent architecture Lead system design discussions and own key architectural decisions, ensuring solutions align with the overall system vision Build and maintain customer-facing APIs with a strong focus on usability, performance, and reliability Ensure high-quality delivery through testing, monitoring, and debugging in production environments, including systems with non-deterministic (LLM-driven) behavior Mentor engineers through code review, design feedback, and pairing, and help grow the team's technical capabilities Collaborate with engineers, product managers, and domain experts to deliver end-to-end features Continuously improve system performance, scalability, and operational efficiency Leverage AI-assisted development tools to improve development speed and code quality Who are you? What We’re Looking For: Proven experience as a technical lead or in a senior engineering role, with strong backend development skills and a track record of owning systems end-to-end Strong proficiency in Python, with experience building APIs (FastAPI or similar) and backend systems; TypeScript is a plus Experience architecting scalable services and distributed systems, and making tradeoff decisions that hold up under real-world load and change Strong command of API design, data modeling, and system integration patterns — ideally including streaming/event-driven APIs (e.g., SSE, websockets), not just request/response Hands-on experience building or leading development of agentic AI systems: LLM orchestration frameworks (e.g., LangGraph, LangChain), RAG pipelines, or multi-agent architectures Experience working with cloud platforms, ideally AWS (including managed LLM services like Bedrock), and modern CI/CD practices (GitLab CI or equivalent) Experience integrating with external/third-party APIs and handling real-world data and system constraints in production Strong debugging and problem-solving skills in production environments, including systems with non-deterministic (LLM-driven) components Experience mentoring engineers, conducting code/design reviews, and raising the technical bar across a team Ability to break down ambiguous problems into well-defined work, balancing hands-on coding with technical leadership Excellent communication skills, with the ability to align engineering decisions with product and business priorities, and a pragmatic approach to engineering challengesWe are looking for a Lead Software Engineer to build core backend systems powering next-generation agentic AI solutions for the logistics industry. The systems developed by this team optimize deliveries at scale improving driver efficiency, increasing reliability, reducing operational costs, and lowering environmental impact.Design , build, and maintain What We Offer: The opportunity to tackle meaningful and challenging problems A chance to continuously learn and stay on top of the latest technology trends Work that has real-world impact, shaping the future of mobility and technology Regular feedback to help you grow and succeed in your role A collaborative and supportive team environment where your contributions are valued Competitive salary plus bonus Flexible working hours and a hybrid working environment Medical coverage for you and your family This role is eligible for Creative Tax Incentive scheme in Poland” or KUP (Autorskie Koszty Uzyskania Przychodu) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case) Change is HERE. Apply Now! #LI-AK8   #LI-HYBRID Life at HERE in Poland comes with a competitive total rewards package designed to support your health, wellbeing, and performance. This includes a base salary, a Short-Term Incentive (STI) bonus (percentage based on role), a creative tax advantage for eligible positions, private medical care (including dental), life insurance, a meal allowance, vision reimbursement, a remote work allowance (if applicable), access to MyBenefit and Multisport programs, and various wellbeing initiatives. Paid time off, sick leave, and parental leave are provided in accordance with the Polish Labor Code. As part of HERE Technologies employment process, candidates will be required to successfully complete a pre-employment screening process. This offer and any related claims are subject to the successful completion of a pre-employment screening. This will involve employment, education, and criminal verification if applicable. HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics. Who are we? HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely. At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel. Apply for this job online Email this job to a friend Share on your newsfeed Connect With Us! Not ready to apply? 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🏢 Summary: B2B full-stack product engineering cooperation with a strong frontend focus, delivering user-facing hospitality software features from discovery and design through production release. The role combines VueJS-based frontend craft, daily PHP/Laravel backend work, product judgment, UX quality, and AI-augmented development in a remote-first model. 🗂️ Requirements: Strong commercial experience with TypeScript, JavaScript, VueJS, Tailwind, and Pinia, Experience with component architecture, state management, and performance, Documented backend engineering experience with PHP and Laravel, Knowledge of design patterns, APIs, caching, database query optimization, microservices, and message queues, Ability to deliver frontend and backend features end-to-end, Communicative Polish and English 📃 Skills: TypeScript, JavaScript, VueJS, Tailwind, Pinia, PHP, Laravel, Node.js, REST, Docker, GitLab, MySQL, MariaDB, MongoDB, Redis, Microservices, Kubernetes, Claude, Cursor 🏢 Description: The ability to build software is no longer rare. AI has made execution accessible to almost everyone. What's rare now is judgment — understanding customer problems, making sound decisions, and knowing where to create real value. The role At Profitroom we build hospitality software used by thousands of hotels and millions of guests. In this cooperation, you take responsibility for technical initiatives end-to-end: from technical discovery and solution design, through implementation and testing, to release and production readiness. The Product Manager steers direction and owns the what and why. You own the how and the technical solution. This is a full-stack product engineering cooperation with a strong frontend focus . Your technical home is the frontend: user journeys, component architecture, interaction design, and UX quality. You also work across the backend when AI, established patterns, and your experience make it practical — for example, when connecting APIs, implementing business logic, or building integrations. Frontend development and product engineering are not the same thing. Frontend without product judgment is implementation. Product judgment without frontend craft is wireframes. We're looking for both — plus the full-stack reach to deliver a feature end-to-end without handing half of it off. “The builder drives; the PM steers.” This is what we mean by product engineering. Not just a label — a way of working. What you'll actually do Full-stack delivery of user-facing features — the frontend and the backend behind it, designed, built, tested, and shipped by you Technical discovery — together with the PM, you validate feasibility, identify constraints, and shape the technical approach before scope is locked End-to-end quality — you care whether the experience works in production, not only whether it passed review AI-augmented development — Claude Code is our daily driver; MCP servers, custom agents, and internal tooling are part of the real workflow Close collaboration with Product Managers and backend engineers — you own the how; the PM owns the what and why UX coherence — you notice recurring issues, raise them, and leave the product better than you found it → Tech stack Full-stack, TypeScript, JavaScript,VueJS , Node.js, Claude Code, MCP servers, AI agents, REST API, Docker, GitLab CI/CD, PHP, Laravel, MySQL / MariaDB, MongoDB, Redis, Microservices, Kubernetes. What we're looking for: Technical expectations: TypeScript & JavaScript, VueJS, Tailwind and Pinia — strong commercial experience; component architecture, state management, performance; you've built real things with these technologies. UX sensibility — you notice what's wrong before users complain; interaction quality matters to you. PHP & Laravel — you have documented experience with backend engineering, you understand concepts like design patterns, APIs, caching, database query optimization, microservices, message queues. It’s a full-stack job, writing backend will not be an occasional favour but your daily task. AI tooling — hands-on Claude Code, Cursor, or equivalent; experience generating backend integrations with AI and understanding advanced topics like skills, spec-driven developmen, feedback loops; is a strong plus. Communicative Polish and English — you work closely with PMs, QA, and software engineers. You'll enjoy collaborating with us if: You've shipped user-facing features that real people used — and you know what broke and why You notice UI details that most engineers scroll past, and it bothers you when they're wrong You get curious about the business reason behind a feature before you start building it Taking responsibility for a feature end-to-end — from the PM conversation through to production — feels like the natural way to work AI tools feel like a natural extension of how you work; you use them to move beyond the frontend boundary into full-stack work when needed You care about what happens on a slow connection, with a keyboard, and on a screen size nobody designed for You can weigh in on whether a feature is worth building without needing to be the person who makes the final product decision Bonus points: You have a side project — something you built, shipped, and perhaps use yourself You use AI tools on your own account, not only when they are provided as part of a project You've worked with or contributed to a design system or component library You've built Node.js services or backend integrations beyond the occasional CRUD endpoint Probably not for you if: Your definition of “done” is a Figma-accurate implementation, regardless of how it actually works for users Backend is someone else's problem and that's a firm boundary for you Your hands-on AI experience is mostly autocomplete and the occasional PR summary Contract terms: B2B cooperation. Monthly compensation range: 15,000–25,000 PLN net , depending on experience and the agreed scope of services. Remote-first collaboration model International technology and product projects Flexible project collaboration setup Planned service breaks aligned with contract terms Opportunity to collaborate with experienced product and technology teams Opportunity to access selected knowledge-sharing initiatives → Recruitment process Intro call with the Recruiter (up to 45 minutes). We cover your background, what you're looking for, and mutual fit. Technical interview with the Team Leader, Tech Lead, and Product Manager (up to 90 minutes). Expect concrete technical questions and a discussion of how you approach frontend architecture, full-stack delivery, product ownership, and the practical use of AI. We care about judgment and initiative, not keyword recall. Technical task. A time-boxed, practical challenge reflecting the type of services involved in the cooperation, reviewed together in a follow-up call. We care about your process, UX decisions, and how you handle the parts that go beyond the frontend.

🏢 Summary: Backend Engineer role focused on building and operating the AI inference and orchestration layer for production mobile and desktop features. The position emphasizes reliable multi-step AI workflows, low-latency/high-throughput performance, and end-to-end operational ownership of high-traffic APIs. 🗂️ Requirements: Proven experience building and operating high-throughput, low-latency production backend services, Practical experience with AI inference patterns, including LLMs, embeddings, or multimodal systems, Experience integrating OpenAI, Anthropic, or open-source models, Ability to debug distributed backend architectures under heavy load, Experience owning production systems, metrics, monitoring, and incident response 📃 Skills: Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, Embeddings, SQL, NoSQL, Kubernetes, Docker 🏢 Description: Our client is seeking a high-caliber Backend Engineer to own the critical inference and orchestration layer that powers every single AI interaction in the platform. You’ll sit right between state-of-the-art models and millions of user interactions, where latency, correctness, and absolute reliability determine product success. What You’ll Be Doing Inference & Orchestration: Design, build, and scale the core orchestration layers, service boundaries, and inference pipelines that serve production AI features across mobile and desktop apps. Tame Non-Deterministic AI: Build high-reliability, long-running workflows that handle multi-step reasoning, external tool interaction, and persistent context despite non-deterministic model behavior. Performance Optimization: Drive low-latency and high-throughput across inference, caching, batching, and streaming strategies. Production Excellence: Own end-to-end operational quality—from monitoring, logging, and alerting to rapid incident response for high-traffic API endpoints. What We’re Looking For Solid Backend Fundamentals: Proven track record building and operating high-throughput, low-latency production services. AI/LLM Familiarity: Practical experience with AI inference patterns (LLMs, embeddings, multimodal systems) and integrating providers like OpenAI, Anthropic, or open-source models. Distributed Systems Mastery: Comfortable debugging distributed backend architectures under heavy load. Product-Minded Execution: A strong bias toward shipping fast, learning from production metrics, and taking full ownership of your systems. Tech Stack Languages: Python, Node.js AI/ML: PyTorch, OpenAI / Anthropic APIs, Open-Source LLMs Data: SQL & NoSQL databases Infra & Ops: Kubernetes, Docker, modern cloud architecture

🏢 Summary: Backend Engineer role focused on building and operating the AI inference and orchestration systems behind a production AI assistant. The position emphasizes low-latency, high-throughput APIs, distributed-system reliability, observability and performance optimization for mobile, desktop and machine-learning integrations. Remote-first collaboration is available for a candidate working from Poland, with base salary and equity assessed individually. 🗂️ Requirements: Production backend engineering experience, High-throughput, low-latency service experience, AI inference familiarity: LLMs, embeddings, multimodal models, Distributed-systems debugging under load, Production observability and incident-management knowledge, Performance-optimization expertise, Independent delivery in ambiguous environments, Working from Poland, Working-hours overlap with immediate team 📃 Skills: Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, Embeddings, SQL, NoSQL, Kubernetes, Docker, APIs, Caching, Batching, Streaming, Logging, Alerting 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role As a Backend Engineer specializing in AI systems, you will own the inference and orchestration layer behind the product’s AI interactions. Your work will sit between models and end users, where latency, correctness, reliability and operating costs directly affect the product experience. You will build and operate production systems that transform model capabilities into fast, stable and observable APIs used by mobile and desktop applications. What you will do Build and operate backend systems serving AI-powered functionality in production. Design inference pipelines, orchestration layers and service boundaries around Machine Learning models. Take ownership of production monitoring, logging, alerting and incident response. Optimize latency and throughput across inference, caching, batching and streaming. Build reliable APIs supporting integration with mobile, frontend and Machine Learning systems. Diagnose distributed-system issues under production load. Continuously improve system performance and reliability using real-world production signals. What we are looking for Strong backend engineering fundamentals supported by experience with production systems. Experience building or operating high-throughput, low-latency services. Familiarity with AI inference patterns, including LLMs, embeddings and multimodal models. Confidence debugging distributed systems under load. Understanding of production observability, incident management and performance optimization. A delivery-oriented mindset focused on shipping, observing production behavior and improving through iteration. Ability to work independently and make pragmatic engineering decisions in an ambiguous environment. What success looks like Backend systems reliably handle production AI traffic at scale with low latency and high throughput. APIs remain stable, clear and easy to integrate with frontend, mobile and Machine Learning systems. Production incidents are detected quickly, diagnosed effectively and resolved with minimal impact on users. System performance and reliability improve continuously based on real-world usage and production data. Technology stack Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with backend, Machine Learning, mobile and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Staff AI Productivity Engineer role focused on improving AI-assisted software development through autonomous cloud environments, agent integrations, tooling, and documentation. The position owns the internal AI development experience end-to-end, working across CI/CD, infrastructure, internal systems, and application code. Compensation is $180,000–$400,000 USD plus equity under a remote-first policy. 🗂️ Requirements: Strong software engineering fundamentals, Hands-on experience with AI coding agents, Experience creating agent documentation, custom instructions, or context files, Track record of building developer tools or infrastructure used by engineers, Ability to work across CI/CD, cloud infrastructure, internal tooling, and application code 📃 Skills: Backend, Cloud, CI/CD, Infrastructure, Documentation, Claude, Cursor, Copilot, Devin, TypeScript, JavaScript, Go, GraphQL, MCP, CircleCI, Slack, Datadog, GitHub 🏢 Description: About Hightouch Hightouch is an Agentic Marketing Platform powered by the industry-leading Composable CDP. With complete brand context, customer data, and performance history in one place, every marketer finally has the power to build and ship end-to-end campaigns themselves. Teams move faster, stay on brand, and get AI marketing that actually works. Founded in 2019 and headquartered in San Francisco, Hightouch enables marketing teams to analyze performance, brainstorm ideas, and generate creative at a speed and quality that wasn't previously possible. Named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, Hightouch is trusted by leading enterprises like Domino's, Spotify, Aritzia, Cars.com, Ramp, and PetSmart. At Hightouch, our mission is to help our customers leverage data and AI to grow their businesses. The team is ambitious, impact-driven, efficient — and we believe humility, kindness, and compassion are essential to our success. If you're energized by velocity, obsessed with raising the bar, and want to build alongside people who care deeply about each other and our customers, we'd love to meet you. About the Role We are looking for a Staff AI Productivity Engineer to accelerate how our engineering organization works with AI coding tools. This is a hands-on technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase. AI tools are evolving rapidly, and we believe the companies that invest in making agents truly productive - not just available - will have a significant advantage. You'll own this problem end-to-end: from setting up cloud development environments where agents can run autonomously, to building MCP integrations that give agents access to our internal systems, to creating the documentation and context that helps agents understand how we build software. You'll have the hands-on acumen to do a lot of the heavy lifting yourself and the leadership skills to drive cross-team efforts to raise the bar everywhere. This role is a companion role to our Developer Productivity role but has a distinct focus: while Dev Productivity owns the build/test/deploy pipeline, you'll own the AI-assisted development experience. An exceptional candidate could wear both hats. Some of the problems we'll be working on include: Own the agentic development environment: Ensure agents can operate in independent cloud-based development environments, execute our full test suites, examine build results visually, etc Build our tooling integrations: Build MCP server integrations that connect our agents to the systems needed to build and debug software, such as CircleCI, Slack, Datadog, Github, etc Documentation and context: Own our repo-wide agents.md file and work with teams to ensure our library of agent guidance and skills is continually pushing the bar. Ensure our conventions and package structures are exposed in ways that agents can effectively use Enablement: Work with our engineers to understand where agents are struggling and address root causes such as better docs, tooling access, etc. Develop tooling for non-engineers to make simple visual updates to our application Serve as a "PM" for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of what is state-of-the-art in industry and driving those improvements across Hightouch We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10 year post-termination exercise window. About You You are an engineer with a passion for solving hard technical problems that generate real value for customers. You're motivated by high ownership and are comfortable in a fast-paced, startup environment. Must have Strong software engineering fundamentals—you can dive into complex backend code and understand it quickly Deep hands-on experience with AI coding agents (Claude Code, Cursor, Copilot, Devin, or similar) Experience writing effective agent documentation, custom instructions, or context files that meaningfully improved agent output Track record of building developer tools or infrastructure that other engineers actually use Comfortable working across the stack: you'll touch CI/CD, cloud infrastructure, internal tooling, and application code Nice to have Experience building or contributing to MCP servers or similar agent-tooling integrations Background in developer productivity, platform engineering, or developer experience roles Experience with our stack: TypeScript/JavaScript monorepos, Go, GraphQL You've set up sandboxed or containerized development environments at scale Interview Process Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. We will ask you questions, but we want you to ask us questions! Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We don't ask you to write code to solve technical brainteasers that don't appear in your day to day job. Apply: Curl jobapi.hightouchdata.com on port 13784 and have followed those instructions before applying. It'll only take a minute! Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit System Design Screen [45m]: Designing a data processing feature end-to-end AI Skills Interview [60m]: We'll dive into how you leverage AI and how you've helped others do the same Hiring Manager Interview [45m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical E-Verify Statement Hightouch participates in E-Verify. After you join the team, we'll verify your eligibility to work in the U.S. by submitting information from your Form I-9 to the Social Security Administration and, if needed, the Department of Homeland Security. This process happens post-hire only — we never use E-Verify to pre-screen applicants. E-Verify Notice E-Verify Notice (Spanish) Right to Work Notice Right to Work Notice (Spanish)

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience across frontend and backend systems, System design, distributed applications and API architecture knowledge, Experience with LLMs, RAG systems or AI-powered applications, Ability to own features from concept through production deployment, Pragmatic decision-making in ambiguous, fast-moving environments, Cross-functional collaboration with engineering, Machine Learning and product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.

🏢 Summary: Full Stack Engineer role focused on building an AI-native assistant that delivers reliable, persistent, goal-oriented workflows. The position covers frontend, backend and AI integrations, including agent planning, external-tool use, LLM reliability and real-time interactions in a remote-first global team. 🗂️ Requirements: Professional full-stack engineering experience, Frontend and backend systems experience, System design expertise, Distributed applications knowledge, API architecture knowledge, LLM, RAG or AI-powered application experience, Production deployment ownership, Cross-functional collaboration with Engineering, Machine Learning and Product teams 📃 Skills: Next.js, Python, Node.js, PyTorch, OpenAI, Anthropic, LLMs, RAG, SQL, NoSQL, Kubernetes, Docker, APIs 🏢 Description: About the product Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input. The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users. About the role We are looking for a Full Stack Engineer specializing in AI systems to build the product layer that transforms advanced AI capabilities into useful, production-grade workflows. You will help design how AI agents plan and operate, interact with external tools, manage failures, recover from errors and deliver consistent value to users. This is an end-to-end engineering role covering frontend development, backend systems and AI integrations. What you will do Build end-to-end product functionality across frontend, backend and AI integrations. Design agent workflows covering planning, tool use, multi-step execution, failure handling and recovery. Integrate LLMs, memory systems and external tools into applications that operate reliably under real-world conditions. Design real-time AI interactions involving streaming, partial results and strict latency requirements. Improve system reliability, observability and fallback mechanisms. Collaborate closely with Machine Learning, backend and product teams to deliver functionality from concept to production. Continuously improve the product based on real-world usage, evaluation results and observed failure modes. What we are looking for Strong professional experience in full stack engineering across frontend and backend systems. Solid understanding of system design, distributed applications and API architecture. Experience working with LLMs, RAG systems or other AI-powered applications. Ability to operate effectively in ambiguous situations and make pragmatic engineering decisions. Strong ownership and the ability to take functionality from an initial idea through implementation and production deployment. Confidence working in a fast-moving environment with evolving product requirements. Ability to collaborate effectively across engineering, Machine Learning and product teams. What success looks like AI-native product features progress beyond basic chat interfaces into persistent, goal-oriented workflows. Agent workflows reliably complete multi-step tasks across external tools and multiple user sessions. AI interactions remain responsive and achieve low latency without compromising output quality. Production systems include robust fallback and recovery mechanisms for LLM and external-tool failures. The reliability and completion rate of AI workflows improve through continuous evaluation, monitoring and iteration. Reusable patterns and abstractions support scalable integration of LLMs, memory and external tools. The resulting product experience feels proactive, consistent and dependable to users. Technology stack Next.js Python Node.js PyTorch OpenAI, Anthropic and open-source LLMs SQL and NoSQL databases Kubernetes Docker Compensation and employment The position is offered under an employment contract. The company does not publish a fixed external salary range. Compensation is assessed individually based on: professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, expected impact on the product and organization. Candidates may share their expected compensation at the beginning of the recruitment process. The compensation package consists of a base salary and equity, with flexibility for exceptional candidates. A company laptop will be provided where required for the role. Remote work and global collaboration The company operates as a remote-first, globally distributed organization. There is no fixed company-wide working schedule and no requirement to follow one specific time zone. Team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively. The successful candidate will work from Poland and collaborate with frontend, backend, Machine Learning and product specialists located across different regions. Poland-based employees join existing global teams rather than a separate local team. The exact reporting line and hiring manager will be confirmed during the recruitment process. How the team works The company believes that outstanding products are built by small, highly capable and hands-on teams. Decisions are made collaboratively, while individuals are expected to take ownership, bring structure to ambiguous problems and execute independently. The team moves quickly while balancing production quality, experimentation and continuous learning from real user behavior. There is no fixed hiring quota for this position. The company is focused on identifying engineers who meet its technical and ownership standards rather than filling a predetermined number of seats. Recruitment process The standard recruitment process consists of up to four stages: Technical assessment, where relevant to the candidate’s background. HR interview. One or more technical interviews. Founder or leadership interview. Particularly strong candidates may be fast-tracked directly to the technical interview stage based on their experience and previous work. Applications are evaluated by members of the technical team. Interviews may be conducted virtually and, where relevant, onsite. The exact format and interviewers may vary. The company aims to make decisions efficiently and provide candidates with a prompt outcome.