Python AI Engineer at Deloitte, London, 6 Months, £Competitive Day Rate

Job Title: Python AI Engineer

Location: London

Duration: 6 months

Contract Start Date: 12 October

Day Rate: Competitive (Inside IR35)

Deloitte

Working with the Deloitte Associate (Contractor) Programme means we can offer you the opportunity to work on a variation of industry and client related projects. Our aim is to retain the best talent and so when your project end date nears our team of Talent Community Advisors will be working with you to look at alternative projects within the firm that suit your experience should you wish to continue with Deloitte.

The Role

Successful candidate will develop modular Python services across question planning, AI workflow orchestration, information retrieval, evidence processing, LLM integration, response generation and validation. You will work collaboratively with engineering, data, platform and evaluation specialists to translate AI concepts and experiments into reliable, scalable and maintainable production services.

This is a hands-on software engineering role requiring strong production Python experience and practical delivery of Generative AI and RAG systems.

Key Responsibilities

• Design, develop and maintain production-grade Python services for Generative AI and complex RAG solutions.

• Define typed application, API and model contracts.

• Integrate LLMs using structured outputs, tool calling, schema validation, context management and controlled fallback mechanisms.

• Implement multi-stage retrieval using vector search, lexical search, hybrid retrieval, metadata filtering, reranking and evidence selection.

• Build asynchronous services with appropriate timeout, retry, cancellation and exception-handling controls.

• Develop automated unit, integration, contract, regression and failure-path tests.

• Implement structured logging, tracing and operational metrics across AI workflows.

• Monitor and optimise response quality, latency, token usage, cost, concurrency and memory utilisation.

• Translate evaluation findings and production issues into measurable improvements and regression tests.

• Contribute to technical design, code reviews, engineering standards and production support.

Essential Skills and Experience

• Strong commercial experience developing production-grade Python applications and services.

• Advanced Python skills, including asynchronous programming, type annotations, modular design, exception handling, profiling and performance optimisation.

• Strong hands-on experience with Generative AI orchestration frameworks (Pydantic, LangGraph, MS Agent Framework/Semantic Kernel) including typed models, nested schemas, custom validation, serialisation and schema-constrained LLM outputs.

• Demonstrable experience delivering Generative AI and RAG solutions beyond the proof-of-concept stage.

• Strong understanding of embeddings, vector, graph and lexical search, hybrid retrieval, query decomposition, chunking, metadata filtering, reranking and evidence selection.

• Experience integrating LLMs using structured outputs, function or tool calling, prompt and model versioning, token management, response validation and fallback strategies.

• Experience building multi-step, agentic or workflow-based AI applications.

• Strong automated testing experience using Pytest or equivalent frameworks.

• Experience with APIs, distributed services, Git, CI/CD, containers and production observability.

• Experience implementing structured logging, distributed tracing and operational monitoring.

• Strong troubleshooting skills across application behaviour, retrieval quality, model execution, concurrency, memory usage and performance.

Technical Skillsets

• Experience with Azure OpenAI, Azure AI Search or equivalent AI and enterprise search platforms.

• Familiarity with Pydantic AI, LangGraph, Semantic Kernel or similar orchestration frameworks.

• Experience with LLM and RAG evaluation approaches (Azure toolset preferred: Azure Foundry, ML Studio etc.).

• Knowledge of retrieval-quality metrics and controlled experiment design.

• Experience with Docker, Kubernetes, telemetry and load testing.

• Knowledge of knowledge graphs, temporal retrieval or document-linkage techniques.

• Experience developing AI solutions within regulated or specialist knowledge domains.

• Understanding of Generative AI monitoring and protection frameworks (preventing prompt injection, misuse and monitoring costs, tokens, update etc.)

IR35

As a means of managing tax, commercial and reputational risks, Deloitte prohibits the use of Associates through Personal Service Companies (‘PSCs’). All Associates must contract under PAYE arrangements through a Deloitte approved ‘Employment Company’ (aka ‘umbrella company.’)