Tech Lead AI Engineering (m/w/d)

For a young company in the rapidly growing AI implementation market, we are looking for a Tech Lead, starting as soon as possible, ideally in early November. The company runs LLM-based systems in production: content generation pipelines, retrieval-augmented generation (RAG) on internal documents, and automated workflows closely integrated with their business systems. The entire stack is built on TypeScript and Next.js.

These systems are already live. As Tech Lead, you take ownership of them, increase their reliability and quality, and expand them to new use cases, while being technically responsible for a team. The role brings together applied LLM engineering and solid backend engineering in TypeScript. Training or fine-tuning foundation models is not part of the job.

Stack: TypeScript, Next.js, Node.js, Postgres with pgvector, Docker, Azure, Anthropic and OpenAI APIs, Vercel AI SDK.

What you’ll do

Technical responsibility for the team, including architecture decisions and code reviews

Technical guidance for the team and point of contact for non-technical colleagues

Take over and maintain the existing LLM pipelines: review the current architecture, identify failure modes, prioritise fixes, and refactor and extend the systems without disrupting production

Own the RAG systems from end to end: document ingestion and parsing, chunking, indexing, hybrid retrieval (BM25 and vector), query rewriting, reranking and grounded generation with citations

Implement and maintain chunk-level access control, index freshness and tenant isolation across all retrieval systems

Develop content generation pipelines that deliver consistent quality at scale, including human review steps

Build and run automated workflows against internal and third-party business systems (ERP, CRM, email, internal APIs), with durable and idempotent execution, retry and dead-letter handling, and approval steps for irreversible actions

Set up an evaluation framework for systems that currently run without one: golden datasets based on real production failures, retrieval metrics and more

Implement observability along the entire request path

Optimise cost and latency through prompt caching, batching, model routing and smaller models where it makes sense

Identify where deterministic logic is the better choice and implement it accordingly

Work directly with non-technical colleagues to define and validate automated processes

What you bring

Professional experience with at least one LLM-based system in production, including responsibility for its operation and incident handling

Advanced TypeScript and Node.js skills: strict typing of non-deterministic model output, async and concurrency patterns, streaming responses, structured error handling

Production experience with Next.js: App Router, route handlers, server actions, streaming to the client

Proven track record of taking over and improving existing codebases under production traffic

Hands-on retrieval expertise: hybrid search, choosing embedding models, cross-encoder reranking, metadata filtering, permission-aware retrieval and structured diagnosis of poor retrieval quality

Experience working with real-world documents: PDFs with tables, scanned material, DOCX, HTML, including layout-aware parsing, OCR and evidence-based chunking

Structured outputs and tool calling are part of your daily work: JSON Schema, Zod or similar runtime validation, function calling, handling malformed or partial output, context window management

Experience designing and running LLM evaluations

Experience with LLM tracing and evaluation tools in a TypeScript codebase (e.g. Braintrust, Langfuse, Promptfoo, OpenTelemetry or Arize Phoenix)

Familiarity with Postgres including vector search (pgvector or a comparable vector store), Docker, Git, CI/CD and at least one major cloud platform

Practical experience with the Anthropic and/or OpenAI TypeScript SDKs

Confident communication in English, German is a plus

Nice to have

Durable workflow execution for long-running, unattended processes (Temporal, Inngest or similar)

Agent orchestration in production, tool calling, recovery, multi-step workflows (Vercel AI SDK, LangGraph, Mastra, Claude Agent SDK, MCP TypeScript SDK)

Experience integrating enterprise systems such as ERP or CRM platforms like SAP

Security and data protection in LLM systems, defences against prompt injection and data exfiltration, PII handling, GDPR-compliant design, EU-hosted or self-hosted inference

Structured or graph-based retrieval for entity-heavy dataexperience

Migrating live pipelines to a new model, embedding model or index without loss of quality

Azure DevOps, Pipelines, Repos and Boards

Benefits

Hybrid setup with 2 office days per week in a bright office in Cologne’s Belgian Quarter (with two balconies and the best view of the city ;))

AI implementation, the growth market of the coming years

Trust-based working hours with compensation for overtime

Lots of creative freedom and space for your own ideas

Continuous professional, strategic and technological development

An open feedback culture, transparent communication and short decision-making paths

Regular team events and workations

Salary from €60,000 gross per year, with room for more depending on experience

The company is an international team and is actively committed to an inclusive workplace. Applications from people of every gender and identity are welcome, regardless of origin, age, religion, sexual orientation or disability. As women remain underrepresented in tech, women are especially encouraged to apply.

We look forward to receiving your application!