Artificial Intelligence Engineer

83data; England; On-site; GBP 70,000 - 90,000; Full time

Job summary

A technology firm specializing in defence solutions is seeking an SC Cleared AI Engineer to develop fully on-premises RAG systems. The role involves building pipelines using open-source technologies and requires expertise in deploying AI capabilities on air-gapped infrastructure. Candidates must have experience with GPU orchestration and strong Python skills, along with SC clearance.

Qualifications

• Active SC Clearance (willingness to undergo DV if required).
• Experience deploying open-source LLMs on-premises.
• Ability to work on air-gapped systems without external resources.

Responsibilities

• Build end-to-end RAG pipelines on isolated defence networks.
• Deploy local vector stores and establish sensitive document ingestion.
• Host and optimise LLMs on local GPU clusters.

Skills

Deployment of open-source LLMs

Experience with local vector databases

vLLM/Text Generation Inference

Python expertise

Tools

Chroma

FAISS

Mistral

NVIDIA A100/H100

Job description

Overview

AI Engineer - Defence RAG Systems ( Security Clearance Essential ) On Site 2 X Days a week Plymouth - willingness to undergo DV if required

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