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AI Engineer

McCabe & Barton Londres, Royaume-Uni
Mise en ligne il y a 4 jours Hybride Intérim £600 - £900

AI Engineer

McCabe & Barton Londres, Royaume-Uni
F
Mise en ligne par
Fiona Eddy
Recruiter

AI Engineer

Software Engineering background is required

London, UK | Hybrid - 3 days in office - 12-month contract (Inside IR35)

We are seeking a AI Engineer with Software Engineering background to join a fast-moving team working across AI platform engineering and direct collaboration with the Investment Team.

The role is split approximately 60/40 between platform engineering and business-facing AI delivery, focusing on building and deploying production-grade AI solutions.

We are looking for someone who writes clean, production-quality code and can turn AI capability into real business impact.

Key Responsibilities

Responsibilities

  1. Design, build and maintain core AI platform components - LLM gateway, MCP connector layer, observability tooling, and privacy Proxy
  2. Develop and harden MCP connectors across data sources (M365, Salesforce, Moody's, internal systems) through PoC, pilot, and GA stages
  3. Build AI-powered tools and workflows for business teams, translating use cases into governed, production-ready applications
  4. Integrate with Databricks/Unity Catalog as the data foundation for AI features
  5. Contribute to spec-driven development practices - writing clear specifications before building, with appropriate test coverage
  6. Support prompt engineering, evaluation, and iterative improvement of deployed AI features
  7. Collaborate with the engineering squad to displace outsourced delivery with in-house capability

Skills/Experience

  1. Hands-on experience building with LLM APIs (Anthropic, OpenAI or similar) in production environments
  2. Experience building AI Solutions is essential
  3. Experience with agentic frameworks, tool use, and MCP or equivalent connector patterns desirable
  4. Familiarity with observability and evaluation tooling for AI systems
  5. Understanding of data platforms - Databricks or similar - and how to expose data safely to LLMs
  6. Security and governance awareness: prompt injection, data boundary controls, RBAC
  7. Comfortable working in a small, high-trust team where you own things end to end
  8. Python development skills is essential
  9. Financial services or regulated environment experience

Référence  JSAI
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