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Founding Engineer
vor 2 Wochen
About the Role
We're building context/fab, a venture-backed industrial AI startup on a mission to upgrade manufacturing by solving the hardest data problems on the shop floor.
As our Founding Engineer (Knowledge Graph / AI Systems), you'll architect and build the intelligence layer that powers our platform — from graph-based RAG to agentic workflows to robust LLM evaluation pipelines. You'll work directly with the founders to define how industrial knowledge is modelled, retrieved, reasoned over, and validated across real-world factory environments.
This is a deeply technical, high-ownership role for someone who wants to invent and ship the core AI systems behind a category-defining product.
What You'll Do
- Design and build our industrial knowledge graph: schema, ontology, data modelling, ingestion, enrichment, and versioning
- Architect and implement graph-based RAG pipelines, retrieval strategies, and hybrid search
- Develop agentic workflows that orchestrate tools, models, and data sources across the manufacturing stack
- Build and maintain rigorous LLM evaluation, benchmarking, and performance testing methodologies
- Develop scalable Python systems for data transformation, embedding pipelines, prompt strategies, and model routing
- Work with real factory data — noisy, unstructured, multimodal — and turn it into structured context for reasoning
- Collaborate closely with fullstack/infrastructure/edge teams to integrate graph/RAG/agentic systems into production services
- Work with edge-connectivity and ingestion teams to model data flowing from real-time factory systems into the graph
- Prototype, experiment, and ship improvements to model quality, latency, reliability, and grounding
- Act as a true partner to the founders — defining our AI direction, research priorities, and technical strategy
What Makes You a Great Fit
- Strong experience in Python and building production-grade data/AI systems
- Experience with knowledge graphs (Neo4j, FalkorDB, or similar)
- Be product-minded and excited about deeply understanding customer problems without being spoon-fed requirements
- Deep familiarity with retrieval systems, embeddings, semantic search, or vector stores
- Experience with LLM evaluation, testing harnesses, model benchmarking, and reliability engineering
- Hands-on experience with RAG pipelines, prompt engineering, and agent frameworks is a big plus
- Comfort working with messy, heterogeneous real-world datasets
- Understanding of distributed systems, data modelling, or ETL/ELT pipelines
- Exposure to Go/Rust ecosystems is helpful
- Pragmatic: you care about shipped impact, not research for its own sake
- Entrepreneurial — you want to build foundational systems at the earliest stage of a company
- Fluent in English; German is a plus
Qualifications
- Bachelor's or Master's in Computer Science, Engineering, AI/ML, Data Science, or related field
- Strong communication and collaboration skills
- Comfortable working independently in a high-ambiguity, high-velocity environment
Why Join Us
- Lead core engineering efforts and shape both product and architecture from day zero
- Work directly with founders at the earliest stage of a startup
- Build at the intersection of AI, manufacturing, and data — solving problems with huge real-world impact
- Excited about building up deep tech capabilities to keep manufacturing competitive in Europe
- Shape our engineering culture in our Munich office
- Competitive salary and meaningful early equity
- Grow faster than anywhere else — experience a 10-year career in 2 years
