Key skills
AngularCloudJavaNumpyPandasPostgresPythonScikit-LearnSpringAILLMLangChainscikit-learnNumPyPineconeWeaviate
About this role
Role Overview
- Design, secure, extend, and customize system prompts; evaluate the impact of prompt changes and continuously improve LLM usage scenarios while analyzing risks and benefits.
- Design and optimize retrieval pipelines, including document chunking, embedding generation, and ranking strategies.
- Build and maintain solutions using vector databases (e.g., FAISS, Weaviate, Pinecone) or Postgres with pgvector, to enable accurate and context-aware responses.
- Implement advanced context window optimization, memory strategies, and token efficiency techniques to ensure scalable and cost-effective LLM interactions.
- Evaluate new LLM releases, monitor response quality and consistency, and build automated evaluation pipelines to assess performance across use cases.
- Design and implement prompt injection protection, output filtering, and policy enforcement mechanisms to ensure safe and compliant AI behavior in enterprise environments.
- Develop and expose AI capabilities via scalable APIs, ensuring proper integration into existing systems and workflows.
- Design and manage serving layers for LLM applications, addressing scaling strategies, latency considerations, and reliability in both cloud and on-prem environments.
- Implement logging, monitoring, and alerting mechanisms to ensure visibility into system performance, usage patterns, and failures.
- Develop prototype and production-level Python code to support AI features, ensuring reliability and maintainability aligned with product requirements.
- Stay up to date with the latest techniques in reasoning, chaining, and context optimization; contribute to AI Labs community discussions and share findings with the Data Science team.
Requirements
- Strong German language skills (B2 level or higher) required
- 4+ years of experience with Python and its data science ecosystem (Pandas, NumPy, Scikit-learn)
- Proven experience in prompt engineering and LLM behavior analysis
- Extensive hands-on experience with LLM integration frameworks such as LangChain or similar.
- Experience designing retrieval pipelines, including chunking, embedding generation, and ranking strategies
- Hands-on experience with vector databases (PG Vector, FAISS, Pinecone, Weaviate, etc.)
- Strong understanding of embeddings and semantic search
- Experience with context window optimization, memory strategies, and token efficiency techniques
- Experience implementing prompt injection protection, output filtering, and policy enforcement mechanisms
- Experience building and exposing APIs for AI systems
- Experience with serving LLM applications, including scaling and latency optimization
- Familiarity with deployment in cloud and/or on-premise environments
- Experience with logging, monitoring, and system observability
- Experience building automated evaluation pipelines for LLM systems
- Nice to have: Experience with Java or modern backend frameworks (e.g., Spring) for enterprise system integration
- Experience with frontend frameworks (e.g., Angular) for building or integrating AI-driven user interfaces
- Familiarity with LLM observability tools or advanced evaluation frameworks
- Experience with real-time or streaming inference systems
Tech Stack
- Angular
- Cloud
- Java
- Numpy
- Pandas
- Postgres
- Python
- Scikit-Learn
- Spring
Benefits
- Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.
- Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.
- Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.
- We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.
- As a growing community in a hybrid environment, we want to ensure we remain connected not just by the great work we do every day but through our passions and interests.