Artificial Intelligence Engineer

A well-funded industrial AI scale-up is hiring a Senior AI Software Engineer as they expand their platform and respond to growing customer demand. They're building technology that turns messy manufacturing data into structured insight — helping factories understand and improve how things are made. With a rising workload, they're adding a hands-on engineer to accelerate delivery.

The Role

Build and ship AI features that transform unstructured operational data into trustworthy, structured knowledge for manufacturers.

Extend and maintain their knowledge graph platform, including adding a time dimension — a core technical challenge.

Design and implement RAG and agentic systems that work reliably in industrial environments.

Own end-to-end delivery: ingestion, embeddings, retrieval, ontology adjustments, deployment and monitoring.

Work closely with a small engineering team (backend, frontend, architecture) to bring AI capabilities into production quickly.

Tackle a 40-item AI backlog and help define how AI is built and scaled inside the organisation.

What You'll Bring

Strong Python engineering skills with experience delivering production AI systems (assumed FastAPI/Flask familiarity).

Practical experience working with structured and unstructured data — beyond notebooks and prototypes.

Understanding of RAG, embedding retrieval algorithms, self-refinement patterns and knowledge graph integration.

Experience adjusting ontologies / column dictionaries for real-world data environments.

Prior experience delivering in production

Familiarity with Neo4j or graph databases and cloud deployment environments

What's On Offer

Salary (UK full-time): £60k–£75k

Hybrid London with periodic Prague visits.

Small, focused team with direct ownership and fast decision-making.

Work on applied AI challenges that matter

Screening Questions

• What production systems have you built that work with unstructured or mixed-format data?
• Describe your experience with RAG, retrieval algorithms or knowledge graph integrations.
• Have you worked on systems requiring ontology or schema adjustments across different environments?