AI Engineer - Defence RAG Systems ( Security Clearance Essential ) On Site 2 X Days a week Plymouth Clearance: Active SC Essential | Sector: Defence Role Overview Defence client requires an SC Cleared AI Engineer to build fully on-premises RAG systems using open-source technologies. You'll develop classified AI capabilities on air-gapped infrastructure with zero external dependencies. Key Responsibilities - Build end-to-end RAG pipelines on isolated defence networks using open-source LLMs (Llama 3, Mistral, Qwen) - Deploy local vector stores (Chroma, FAISS, Milvus) with sensitive document ingestion pipelines - Host and optimise LLMs using vLLM/TGI on local GPU clusters without internet connectivity - Implement agent orchestration using LangChain/LangGraph in completely offline environments - Design secure document processing for classified materials with appropriate data sanitisation - Build monitoring and evaluation systems that operate within air-gapped infrastructure Essential Requirements - Active SC Clearance (non-negotiable) - willingness to undergo DV if required - Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises - Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments - Strong vLLM/Text Generation Inference experience for high-throughput model serving - Proven ability to work on air-gapped systems with no external package repositories - Experience with GPU orchestration (NVIDIA A100/H100) and CUDA optimisation - Python expertise with offline dependency management and local package mirrors Technical Stack (All On-Premises) Models: Llama 3, Mistral, Qwen (locally hosted) Vector Stores: Chroma, FAISS, Milvus Orchestration: LangChain, LangGraph for agents Hosting: vLLM, TGI, Ollama on bare metal/private cloud Infrastructure: Air-gapped Kubernetes, local container registries Desirable Skills - Experience with defence/government IT security protocols - Knowledge of CIS benchmarks and NCSC guidelines - Familiarity with cross-domain solutions and data diodes - Understanding of classification marking and handling procedures