AI Platform Engineer - 24 Months Contract - Part-Time

About the Role

We're looking for an AI Platform Engineer to design, deploy, and operate enterprise-grade AI platforms — not to build models, but to make AI work in production.

You'll be responsible for:

• Deploying and managing LLM hosting, inference services, and embedding services

• Running AI agent orchestration platforms in a regulated on-premises environment

• Managing GPU infrastructure and optimizing model performance (quantization, vLLM, batching)

• Building reusable APIs, SDKs, and shared AI services that other teams can plug into

• Keeping AI systems secure, compliant, and observable

This is a hands-on engineering role. You'll be in the terminal, on Kubernetes, tuning inference pipelines, and shipping production services — not writing research papers or building dashboards.

Who We're Looking For

You must have:

• 2+ years of hands-on experience deploying and managing AI/LLM platforms in production

• Strong Kubernetes skills — you've run AI workloads on K8s, not just deployed a single container

• Experience with GPU infrastructure — managing GPU nodes, scheduling, monitoring

• LLM deployment experience — inference serving, model hosting, prompt pipelines

• Software engineering fundamentals — you write clean APIs, use CI/CD, and containerise your work

• Experience with vector databases and RAG architectures

Nice to have:

• Experience with agentic AI frameworks (LangChain, LlamaIndex, multi-agent systems)

• Model optimisation techniques (quantization, vLLM, batching)

• Experience working in regulated or on-premise environments (gov, defence, finance)

• Background in Computer Science, Computer Engineering, or related fields