Senior Applied AI Engineer

About The Role

RobCo is building the category of Autonomous Industrial Robotics and we're doing it fast. We believe that automating the ordinary frees humans to do the extraordinary, and we're building the end-to-end robotics infrastructure to make that possible - hardware, software, and AI in one stack that just works. As our Senior Applied AI Engineer, you'll build the agentic workflows that run our solution delivery behind the scenes.

Responsibilities

• Design, build, and run agentic workflows across our delivery process - requirements review, automated checks and gates, early risk detection, and a knowledge base that makes everything we've learned from past projects available to agents and people - owning each from concept through production.
• Build the way we build: reusable components, skills, and patterns for tool integrations, feedback loops, and identity, secret, and auth management.
• Own quality end to end: design and run evals, monitor agents in production, and manage observability, cost, guardrails, and security so teams can trust what the agents produce.
• Design human-in-the-loop workflows that learn: people review and correct agent output at defined checkpoints, and those corrections flow back into better prompts, evals, and components, so the agents keep improving.
• Embed with our delivery teams to understand how their work actually flows, identify where agents create the most leverage, and define together what good looks like.
• Drive adoption and help shape how RobCo uses AI internally: deliver agents through the tools teams already use every day, establish best practices, and build paved paths so teams can eventually create their own agents.

Requirements

• Several years of software engineering experience and the seniority to take a problem from ambiguous idea to production system, with clean architecture, solid testing, and maintainable code.
• Shipped LLM-powered or agentic systems that real users depend on, not just prototypes: tool calling, structured outputs, multi-step workflows.
• Deep, practical experience with the agentic stack - orchestration, tool use, MCP, memory, and retrieval - in production environments.
• Strong context engineering and prompt engineering skills: you think carefully about what the model sees and in what structure, you treat prompts as versioned, tested engineering artifacts, and you have a rigorous way of judging whether the output is actually good.
• Built knowledge bases and put RAG pipelines to work. You don't need to be a retrieval specialist; you need to make organizational knowledge reliably available to agents and people.
• Think in terms of systems and user outcomes, not individual scripts and demos, and bring a component mindset: while building the first agent, you're already thinking about the second and the tenth.
• Genuine enjoyment of working with non-engineering teams: understanding their process, speaking their language, and designing automation around how they actually work.
• Strong proficiency in Python and/or TypeScript, plus fluency with SaaS APIs, webhooks, and the practical realities of integrating business systems.
• Ownership of outcomes and a startup way of working: scope intentionally, build smart, ship fast, and prefer pragmatic solutions that ship over perfect ones that don't.

Qualifications

• Experience with LLM-powered or agentic systems that real users depend on, not just prototypes.
• Experience with the agentic stack - orchestration, tool use, MCP, memory, and retrieval in production environments.
• Experience with context engineering and prompt engineering, including building knowledge bases and using RAG pipelines.
• Experience with Python and/or TypeScript, and proficiency with SaaS APIs, webhooks, and integrating business systems.
• Experience with agile methodologies and a startup mentality, including scope management, smart building, and shipping pragmatic solutions.

Skills

• Software engineering experience with several years of seniority.
• Experience with LLM-powered or agentic systems that real users depend on.
• Experience with the agentic stack - orchestration, tool use, MCP, memory, and retrieval.
• Experience with context engineering and prompt engineering, including building knowledge bases and using RAG pipelines.
• Proficiency in Python and/or TypeScript.
• Experience with SaaS APIs, webhooks, and integrating business systems.
• Experience with agile methodologies and a startup mentality, including scope management, smart building, and shipping pragmatic solutions.

Benefits

• Competitive compensation and benefits package - including medical, dental, and vision coverage, plus a 401(k) plan.
• Unlimited paid time off incl. major holidays.
• Company-sponsored onboarding and team offsites in Germany.

Pay

Competitive compensation and benefits package - including medical, dental, and vision coverage, plus a 401(k) plan.

Schedule

Flat hierarchies, open communication, and regular 360° feedback enable fast decisions and support your professional and personal development.