Key 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 data sources (M365, Salesforce, 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
Skills/Experience
- 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
Rate:
£900/day
Location:
London
IR35 Status:
Inside
Remote Status:
Hybrid
Industry:
AI & Machine Learning
Seniority Level:
Not Specified