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