LLM Platform Engineer/Lead (m/f/d)

What you'll do

• Design and build internal AI frameworks, SDKs, and shared libraries
• Enable teams to integrate AI features with minimal friction
• Set up standardized patterns for using LLMs, embeddings, agents, and workflows
• Build reusable components for prompt management, evaluation, observability, and safety
• Define best practices for AI usage, cost control, and reliability
• Evangelise AI internally through documentation, examples, and hands-on guidance
• Rapidly prototype AI-powered features and turn them into reusable building blocks
• Own AI tooling from experimentation to production

Requirements

• Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.)
• Experience with RAG pipelines, embeddings, vector databases
• Familiarity with prompt engineering, prompt versioning, and evaluation
• Experience with AI orchestration frameworks
• Good understanding of AI observability, cost monitoring, and failure modes
• Shipped at least one LLM-powered feature to production and iterated based on telemetry or user feedback
• Comfortable with embeddings, fine-tuning, vector search, tokenisation, and evaluation methodologies
• Familiar with data lakes/warehouses, feature stores, and streaming/batch ETL; cloud (AWS/GCP/Azure)
• Excellent Python skills
• Experience building frameworks, platforms, or developer tooling
• Strong understanding of APIs, services, and system design
• Writes clean, maintainable, production-grade code
• Bias for shipping and iteration
• Can translate AI complexity into simple abstractions
• Comfortable with ambiguity and rapid change
• Thinks in terms of leverage and reuse, not one-off solutions

Tech stack

Benefits