AI Engineer - Automotive

• Drive the architecture, development and optimization of (generative) AI applications with a strong focus on
model evaluation, retrieval-augmented generation (RAG), and prompt engineering.
• Implement end-to-end RAG pipelines (ingestion, chunking, embeddings, retrieval, re-ranking) and integrate them
with internal data sources.
• Design and integrate data storage for AI applications using vector search in Snowflake and relational databases
such as PostgreSQL.
• Analyze and integrate data from various sources, ensuring high data quality and preparing it for effective AIdriven solutions.
• Experiment with LLM models (e.g. OpenAI, Anthropic, Azure OpenAI) to improve performance, reliability and
applicability across business use cases.
• Establish and maintain robust engineering practices for GenAI applications (testing, observability, security,
performance optimization).
• Collaborate closely with our AI platform team to enhance, standardize and scale AI-driven capabilities across the
BMW Group.
• Work closely with different business units, helping them leverage AI models for real-world applications and
continuous improvements.
• Share your expertise in Generative AI, LLM orchestration, and software engineering with other teams,
contributing to knowledge-sharing and innovation within the organization.

• University degree in Computer Science, Engineering, or a related field.
• At least 7 years of professional software engineering experience, with a strong focus on backend or dataintensive applications.
• Strong proficiency in Python and experience building production systems.
• Strong understanding of software development best practices (clean code, unit/integration testing, code
reviews, CI/CD).
• Hands-on experience with LLM APIs (e.g. OpenAI, Anthropic, Azure OpenAI) and LLM orchestration frameworks
such as LangGraph.
• Proven experience with RAG architectures and vector databases / embeddings.
• Experience with data ingestion and preprocessing for LLM applications (ETL, data pipelines, document
processing).
• Experience implementing guardrails, safety checks and evaluation frameworks for LLM applications.
• Familiarity with MLOps or LLMOps concepts and best practices for deploying, monitoring and maintaining AI
models and AI-enabled services in production.
• Strong problem-solving skills and the ability to work in a collaborative, agile environment.
• Excellent English communication skills, both written and spoken.

*We are an equal opportunity employer and value diversity. All employment decisions are made without regard to age, gender, disability, race, ethnicity, religion, sexual orientation, or any other protected characteristic. We encourage applicants from all backgrounds to apply.*