Job Description

Your mission

• Design and ship production-grade AI systems:  Build scalable LLM-based systems, including workflow agents and multi-agent architectures, that run reliably in real-world environments.
• Own AI features end-to-end:  Take responsibility from idea → prototype → evaluation → production, with a strong focus on quality, reliability, and impact.
• Build robust RAG pipelines:  Implement retrieval systems using embeddings, vector databases, and structured data to ensure grounded, high-quality outputs.
• Develop intelligent patient-facing features:  Create systems that turn unstructured patient data into personalized insights and health reports.
• Drive evaluation and quality:  Build and iterate on evaluation frameworks for LLM outputs, retrieval quality, and agent performance.
• Collaborate cross-functionally:  Work closely with product, data, and domain experts to translate real healthcare problems into effective AI solutions.
• Optimize for performance and scale:  Improve latency, cost-efficiency, and robustness of AI systems in production.

Your profile

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field
• Strong experience building LLM-based applications in production
• Excellent Python skills
• Hands-on experience with:
  • RAG systems, embeddings, and vector databases
  • Prompt engineering and structured outputs
  • At least one major LLM framework (e.g. LangChain, LangGraph, LlamaIndex)
• Experience with agent-based systems (e.g. Autogen, CrewAI, or similar)
• Solid engineering fundamentals: clean code, testing, CI/CD, Docker
• Experience with LLM evaluation or search quality is a strong plus
• Familiarity with AWS, GCP, or Azure
• You are execution-focused and pragmatic — you ship and iterate quickly
• You’re comfortable working in ambiguity and fast-paced environments

Why us?

• A compelling product with real edge: mama health is building an AI-driven platform grounded in real patient experiences — highly differentiated and solving real problems in healthcare
• Cutting-edge challenges: Work on real LLM, RAG, and agent systems in production — not just prototypes
• High ownership: You’ll shape core parts of the product and how we build AI systems as a company
• Strong market pull: Work with leading pharma companies on high-impact use cases
• Ownership and growth: Fast learning curve, real responsibility, and the chance to define our AI stack
• Competitive package: Salary + equity
• Berlin-based team: Full in-office collaboration
• Perks: Team events, offsites, Wolt dinners & rides home when working late