Artificial Intelligence Engineer

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

Job summary

A leading data solutions provider is seeking an experienced AI Engineer to develop on-premises RAG systems for a defence client. The role requires SC Clearance and expertise in deploying open-source LLMs in air-gapped environments. The candidate will work with modern technologies like Llama, Mistral, and vector databases, contributing to sensitive projects with high security requirements. This position involves working onsite in Plymouth for 2 days a week.

Qualifications

• Demonstrable experience deploying open-source LLMs (Llama, Mistral, Falcon) on-premises.
• Expertise with local vector databases (Chroma, FAISS, Weaviate) in offline deployments.
• Proven ability to work on air-gapped systems with no external package repositories.

Responsibilities

• Build end-to-end RAG pipelines on isolated defence networks using open-source LLMs.
• Deploy local vector stores with sensitive document ingestion pipelines.
• Host and optimise LLMs using vLLM/TGI on local GPU clusters.

Skills

Active SC Clearance

Experience deploying open-source LLMs

Expertise with local vector databases

Strong vLLM/Text Generation Inference experience

Ability to work on air-gapped systems

Experience with GPU orchestration

Python expertise

Tools

Llama 3

Mistral

Qwen

Chroma

FAISS

Milvus

LangChain

LangGraph

vLLM

Job description

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

Overview

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.

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