AI Engineer

AI Engineer - Defence RAG Systems ( Security Clearance Essential )

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