SC Cleared AI Engineer: GenAI & RAG Specialist (Remote)

Computer Futures; Ribble Valley; Remote; GBP 111,000 - 166,000; Full time

Job summary

Our Client in London is seeking an SC Cleared AI Engineer on a remote contract basis with occasional travel to client sites. You will work in a product squad to design, build and deliver GenAI and Agentic AI solutions, shaping AI workflows and ensuring secure deployment on Azure.

The role is hands-on, focusing on production-grade Python development, LangGraph work, and building end-to-end RAG pipelines with robust guardrails.

Qualifications

• Active SC clearance suitable for a MOD project.
• Strong production-grade Python software engineering.
• Hands-on GenAI, LLM and Agentic AI development.
• Strong LangGraph and RAG experience.
• Prompt engineering and structured LLM outputs.
• LLM/RAG evaluation, testing and hallucination mitigation.
• API and backend service integration.
• Automated testing, error handling and observability.
• Hands-on experience with Azure OpenAI, Azure AI Search and Azure AI Foundry.

Responsibilities

• Build GenAI and Agentic AI applications using Python and LangGraph.
• Develop multi-step workflows involving state, routing, tool use and human review.
• Design end-to-end RAG pipelines covering ingestion, chunking, embeddings, indexing and retrieval.
• Build and integrate APIs and backend services.
• Evaluate LLM quality, grounding and hallucinations, implementing guardrails.
• Handle failures, retries and workflow recovery.
• Implement monitoring, logging and tracing across AI applications.
• Deploy secure and scalable AI solutions on Azure.

Skills

Python

GenAI

LangGraph

RAG

APIs

LLM

Prompt engineering

Tools

Azure OpenAI

Azure AI Search

Cosmos DB

Redis

Key Vault

Azure Monitor

Application Insights

Job description

Our Client in London is seeking an SC Cleared AI Engineer on a remote contract basis with occasional travel to client sites. You will work in a product squad to design, build and deliver GenAI and Agentic AI solutions, shaping AI workflows and ensuring secure deployment on Azure.

The role is hands-on, focusing on production-grade Python development, LangGraph work, and building end-to-end RAG pipelines with robust guardrails.