AI Engineer (m/w/d)
Der Kunde
Our client, based in Cologne, has its roots in web and app development, with a particular focus on building apps and platforms. More recently, the company has shifted its focus towards the integration of AI applications within the enterprise environment. With a clear focus on AI integration, consulting, and conceptualization, the company aims to be at the forefront of the technological revolution.
Zur Rolle
Are you an experienced AI Engineer with a passion for production-grade LLM systems and solid backend engineering? In this role, you will work with LLM-based systems already running in production, including content generation pipelines, retrieval-augmented generation (RAG) over internal documents, and automated workflows deeply integrated with business systems.
The stack is TypeScript and Next.js end to end. As an AI Engineer, you will take ownership of these systems, improve their reliability and quality, and extend them to support new use cases.
The role combines applied LLM engineering with solid backend engineering in TypeScript. It does not involve training or fine-tuning foundation models.
Stack: TypeScript, Next.js, Node.js, Postgres with pgvector, Docker, Azure, Anthropic and OpenAI APIs, Vercel AI SDK
Deine Mission
- Take over and maintain existing LLM pipelines: assess the current architecture, identify failure modes, prioritise fixes, and refactor and extend the systems without disrupting production
- Own our RAG systems 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 retrieval systems
- Develop content generation pipelines that deliver consistent quality at volume, including human review steps
- Build and operate 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
- Establish an evaluation framework for systems currently running without one: golden datasets derived from observed production failures, retrieval metrics, and more
- Implement observability across the full request path
- Optimise cost and latency through prompt caching, batching, model routing and use of smaller models where appropriate
- Assess where deterministic logic is the better solution and implement it accordingly
- Work directly with non-technical colleagues to specify and validate automated processes
Dein Profil
- Professional experience with at least one LLM-based system in production use, including responsibility for its operation and incident handling
- TypeScript and Node.js at an advanced level: strict typing of non-deterministic model output, async and concurrency patterns, streaming responses, structured error handling
- Next.js in production: App Router, route handlers, server actions, streaming to the client
- Demonstrably taken over and improved existing codebases under production traffic
- Practical retrieval expertise: hybrid search, embedding model selection, cross-encoder reranking, metadata filtering, permission-aware retrieval, and structured diagnosis of poor retrieval quality
- Experience processing real-world documents: PDFs with tables, scanned material, DOCX, HTML - including layout-aware parsing, OCR, and evidence-based chunking
- Structured outputs and tool calling as part of your everyday work: JSON Schema, Zod or comparable runtime validation, function calling, handling of malformed or partial output, context window management
- Designed and run LLM evaluations
- Experience with LLM tracing and evaluation tooling in a TypeScript codebase (e.g. Braintrust, Langfuse, Promptfoo, OpenTelemetry/Arize Phoenix)
- Familiar with Postgres including vector search (pgvector or a comparable vector store), Docker, Git, CI/CD, and one major cloud platform
- Working experience with the Anthropic and/or OpenAI TypeScript SDKs
- Confident communication in English; German mind. B2
Nice to have
- Durable workflow execution for long-running, unattended processes (Temporal, Inngest, Trigger.dev or comparable)
- Agent orchestration in production: tool calling, recovery, multi-step workflows (Vercel AI SDK, LangGraph, Mastra, Claude Agent SDK, MCP TypeScript SDK)
- Integration experience with enterprise systems such as ERP or CRM platforms like SAP
- Security and data protection in LLM systems: prompt injection and data exfiltration defences, PII handling, GDPR-compliant design, EU-hosted or self-hosted inference
- Structured or graph-based retrieval for entity-heavy data
- Experience migrating live pipelines to a new model, embedding model or index without quality regression
- Azure DevOps: Pipelines, Repos and Boards
Unser Kunde bietet
- AI implementation – one of the key growth markets of the coming years
- Trust-based working hours with overtime compensation
- Plenty of creative freedom and room for your own ideas
- Continuous development – professionally, strategically, and technologically
- An open feedback culture, transparent communication, and short decision-making processes
- Regular team events and workations
Klingt nach dir? Dann los.
Drei Angaben reichen. Wir melden uns innerhalb von zwei Werktagen und schicken dir das Self-Assessment (ca. 30 Minuten).