AI Backend Engineer (f/m/d)

Tasks

As an AI Backend Engineer, you will build the technical backbone of our Decision Intelligence platform. You develop scalable backend services that bring our forecasting and optimization models, agentic workflows, and our semantic data layer into productive use. You work AI-first: Claude Code or similar CLIs, MCPs, and custom skills are your standard toolkit. You think not only in terms of endpoints and databases, but in customer value, product impact, and adoption & and always eager to strengthen the system and not only solve the task at hand.

• You think in terms of impact and have a strong product mindset: you measure whether your features actually achieve adoption, observe usage patterns, and sharpen the next iteration together with Product and FDE.

• You design, build, and operate scalable backend services in Python with FastAPI and pydantic that productively support agent workflows, forecasting and replenishment.

• You design clean APIs between the platform, agents, ML models, frontend, and customer systems (ERP, BI, planning tools) and ensure robustness and observability.

• You build and extend our semantic data layer as the foundation for accurate forecasts and precise responses from our agents: modeling in PostgreSQL, transformations with dbt, pipelines, caching, and retrieval.

• You integrate LLM and agent systems deeply into the backend: tool use, function calling, RAG pipelines, eval frameworks for LLM outputs, guardrails, and production deployment.

• You work AI-first. Claude Code, AI assisted code development, and subagents are part of your daily toolkit, and you continuously extend our internal setup (CLAUDE, hooks, skills, plan/execute/review loop, plugings, tooling, docs).

• You translate business and customer requirements into viable technical solutions together with FDEs and Product, and make pragmatic trade-offs between speed, scalability, and maintainability.

• You prototype quickly and close to the user: you put new ideas into the hands of FDEs and customers in days rather than weeks, gather early feedback autonomously, iterate closely on the actual workflow, and decide based on real usage what is worth hardening and rolling out.

Requirements

• 2 to 5 years of professional experience as a Backend, Software, or AI Engineer in a product-oriented environment - ideally in a product or SaaS context, startup experience welcome.

• Solid backend foundation: Python with FastAPI and Pydantic, clean API design, asynchronous programming, PostgreSQL and Redis, containerization with Docker, and experience with CI/CD pipelines.

• Strong product mindset: you don't just ask "How do I build this?" but "What are we building this for, for whom, and how will we know it has impact?". You think in terms of users, adoption, and chains of impact, not just tickets.

• Practical experience with LLMs and agent systems: prompt engineering, tool use/function calling, RAG, eval frameworks, and production deployment.

• Experience with cloud infrastructure, ideally AWS, as well as a good feel for Kubernetes and Infrastructure-as-Code with Terraform - you don't need to master everything in your sleep, but you should be able to move confidently in this space.

• High level of ownership, appetite for ambiguity, and motivation to continuously develop yourself in backend engineering, agentic engineering, and your product perspective.

• Clear, compelling communication, both technical and non-technical, with low ego.

• Fluent English, bonus: native German or C1 level.