AI Engineer, webbyfox consultancy

London, UK

We're looking for an AI Engineer to design, build, and ship AI-powered features for our clients' Python web applications. You'll take LLM and machine learning ideas from prototype to production, adding AI search, intelligent agents, and automation to Django and FastAPI products. You'll work closely with our senior Python engineers and with client teams.

Key responsibilities: - Design and build LLM-powered features such as retrieval-augmented generation (RAG), semantic search, chat assistants, and AI agents - Integrate LLM APIs (e.g. OpenAI, Anthropic, Gemini) and open-source models into Django and FastAPI services - Build and maintain data pipelines for document ingestion, chunking, embeddings, and vector search - Engineer prompts, tool and function calling, and multi-step agent workflows - Set up evaluation, testing, and monitoring for AI features, covering quality, latency, cost, and safety - Optimise performance and cost through caching, model selection, and batching - Make sure AI features are secure, privacy-conscious, and compliant with UK GDPR - Work with clients in discovery sprints to find practical, high-value AI use cases - Keep up with the fast-moving AI ecosystem and share knowledge across the team

3+ years of professional Python development experience, including at least 1 year building LLM or ML features used in production

Hands-on experience with LLM APIs and frameworks (e.g. OpenAI/Anthropic SDKs, LangChain, LlamaIndex, or similar)

Solid understanding of RAG architectures, embeddings, and vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar)

Experience building APIs with FastAPI or Django; async Python is a plus

Strong PostgreSQL skills; pgvector experience is a plus

Familiarity with prompt engineering, tool/function calling, and agent design patterns

Experience evaluating and monitoring LLM output (eval frameworks, tracing, observability tools)

Working knowledge of Docker, cloud platforms (AWS, GCP, or Azure), and CI/CD

Good testing discipline with pytest

Understanding of AI safety, data privacy, and responsible AI practices

Clear communication skills and the ability to explain AI trade-offs to non-technical clients

Nice to have: experience with ML fundamentals (PyTorch, Hugging Face, fine-tuning), Wagtail, or open-source contributions

Degree in Computer Science, AI/ML, or a related field, or equivalent practical experience