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# AI Engineer

- **Company:** McCabe & Barton
- **Location:** London, UK
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Code Coverage, Data Infrastructure, Python (Programming Language), Role-Based Access Control, Salesforce.Com, Software Engineering, Datadog, Application Enhancement Tool, Large Language Models, Prompt Engineering, AI Platforms, Data Management, Databricks
- **Published:** September 3, 2026
- **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-7AD18BE6BAD3A8BE4B/

## About the Role

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

## Description

We are seeking a I 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

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


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