Artificial Intelligence Engineer

Wave Talent; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Small focused team

Direct ownership and fast decision-making

Job summary

An industrial AI scale-up in the UK is looking for a Senior AI Software Engineer to help expand their platform. The ideal candidate will build and ship AI features that turn unstructured operational data into structured knowledge for manufacturers. With a focus on delivery, this role also involves extending the knowledge graph platform and integrating RAG systems. Candidates should have strong Python skills and experience with AI production systems. This position offers a hybrid work model and opportunities to tackle real-world AI challenges.

Qualifications

• Strong Python engineering skills with experience delivering production AI systems.
• Practical experience working with structured and unstructured data.
• Understanding of RAG, embedding retrieval algorithms, and knowledge graph integration.
• Familiarity with Neo4j or graph databases and cloud deployment environments.

Responsibilities

• Build and ship AI features that transform unstructured operational data.
• Extend and maintain their knowledge graph platform.
• Own end-to-end delivery: ingestion, embeddings, retrieval, and monitoring.
• 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.

Skills

Strong Python engineering skills

Experience delivering production AI systems

Understanding of RAG and embedding retrieval algorithms

Familiarity with Neo4j or graph databases

Experience with structured and unstructured data

Tools

FastAPI

Flask

Neo4j

Cloud deployment

Job description

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.
• Familiarity with Neo4j or graph databases and cloud deployment environments.

What’s On Offer

• 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?

Seniority level: Mid‑Senior level

Employment type: Full‑time

Job function: Information Technology

Industries: Technology, Information and Media, Manufacturing