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SC cleared - AI engineer

Job Posted: 19 hours ago

  • Salary: £ 600 - 700 / Day

    Job Type: Contract

  • Location: United Kingdom

Expire in: a month

Job Description

Overview A leading defence organisation is seeking an SC-cleared AI Engineer to develop fully air-gapped Retrieval-Augmented Generation (RAG) systems using open-source technologies. This is a rare opportunity to work on highly classified AI capabilities within secure, on-premises environments—no cloud, no external dependencies. Key Responsibilities Architect and deploy end-to-end RAG pipelines using open-source LLMs (e.g. Llama 3, Mistral, Qwen) on isolated defence networks Build and manage local vector databases (Chroma, FAISS, Milvus) for sensitive document ingestion Host and optimise LLMs using vLLM or TGI on local GPU clusters (no internet access) Implement agent orchestration with LangChain/LangGraph in fully offline environments Design secure document processing workflows with robust data sanitisation protocols Develop monitoring and evaluation systems that operate within air-gapped infrastructureEssential Requirements Active SC Clearance (mandatory) – DV clearance willingness is a plus Proven experience deploying open-source LLMs (Llama, Mistral, Falcon) in on-prem environments Expertise with local vector stores (Chroma, FAISS, Weaviate) in offline setups Strong hands-on experience with vLLM or Text Generation Inference for high-throughput serving Comfortable working in air-gapped systems with no access to external package repositories Experience with GPU orchestration (NVIDIA A100/H100) and CUDA optimisation Advanced Python skills, including offline dependency management and local mirrorsTechnical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registriesDesirable Skills Familiarity with defence/government IT security protocols Understanding of CIS benchmarks and NCSC guidelines Experience with cross-domain solutions and data diodes Knowledge of classification marking and secure handling procedures

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