AI Platform Engineer

AI Platform Engineer

5 Contract Roles | Principal, Senior and Mid-Level

£475 per day | IR35 Status TBC

Location: Largely Remote, with Travel to Client Site

We’re partnering with an AI-focused consultancy to appoint five experienced AI Platform Engineers for a major platform programme within a high-traffic, heavily regulated consumer environment.

This is an opportunity to help create the shared foundation behind an organisation’s AI capabilities. You’ll build a scalable platform that product and engineering teams can use by default, with the governance, resilience and cost control required within a regulated business.

Positions are available at Principal, Senior and Mid-Level, with responsibilities and expectations tailored to each level.

The Opportunity

You’ll work across three core areas of the AI platform:

Inference control: Developing the gateway and routing layer connecting engineering teams to multiple LLM providers, including resilient failover and load-shedding capabilities. Orchestration and capability lifecycle: Building tools that allow teams to register, discover, manage and reuse AI capabilities and agents. Trust, safety and governance: Embedding access controls, audit trails, guardrails and cost attribution throughout the platform.

At Principal level, you’ll set the platform’s technical direction and lead architecture discussions with senior engineering stakeholders.

At Senior level, you’ll take end-to-end ownership of a significant platform component and establish the standards required to deliver it successfully.

At Mid-Level, you’ll build and release solutions across the platform alongside experienced engineers, contributing reliable production-quality code.

Key Responsibilities

You’ll play an important role in designing, building and delivering the AI platform by:

Building and evolving the API gateway and routing layer connecting teams to multiple LLM providers. Developing failover, load-shedding and resilience capabilities for periods of provider degradation. Designing orchestration, registration and discovery tooling for reusable AI capabilities. Establishing API design, versioning and promotion workflows to move capabilities from experimentation into production. Implementing RBAC and OIDC-based access controls. Supporting secure API key issuance, rotation and revocation. Applying high standards across testing, observability and technical documentation. Using evaluation frameworks, golden datasets, structured outputs and fallback paths to manage non-deterministic behaviour. Producing architecture decision records, runbooks and API documentation. Supporting knowledge transfer through code reviews, pairing and close collaboration with internal engineering teams. Planning and prioritising your work, managing changing requirements and raising delivery risks early.