Head of Engineering and AI job at London Full Time NEW

Head of Engineering and AI

Leading Buy-Side Investment Firm | London | 12 Months contract position

The Opportunity

Join a leading buy-side investment firm as Head of Engineering and AI , taking ownership of proprietary investment and operations platforms while driving the transformation to AI-augmented development.

This is a hands-on leadership role for an engineering leader who treats software as a craft, has strong opinions on modern application architecture, and is energized by building AI-native delivery capabilities.

What You’ll Own

Proprietary Applications

1. Lifecycle ownership of core investment and operations systems
2. Application portfolio including architecture, technical roadmap, framework modernization
3. Decommissioning legacy components and driving technical evolution

AI-Augmented Delivery

1. Drive adoption of Claude Code , agentic pipelines, and AI-generated testing across the development lifecycle
2. Productionize existing PoCs (unit test generation, codebase documentation, ADO-to-GitHub automation)
3. Build AI-native delivery model reducing external supplier dependency

MCP & Integration Architecture

1. Build MCP connector layer exposing proprietary systems to firm’s AI estate
2. Implement governance, audit trails, and access controls
3. Enable secure, governed AI integration with core platforms

Team & Supply Model

1. Lead small senior in-house engineering squad augmented by selected contractors
2. Set engineering standards, code review culture, and delivery cadence
3. Reduce dependency on external development suppliers through AI-augmented in-house capability

Governance & Audit Readiness

1. Ensure institutional investor scrutiny standards met
2. AI code provenance, container hardening, change control, full audit trails
3. FCA regulated environment compliance without slowing delivery

We’re Looking For

An engineering leader who has done the work, not just managed it.

Essential:

1. Strong track record building and running proprietary applications in financial services
2. Deep .NET background with modernization programme experience
3. Multi-language fluency – .NET, Python, TypeScript, SQL
4. Hands-on AI tooling experience – Claude Code, Cursor, or equivalent AI-native development tools with clear POV on effective use
5. MCP, agent frameworks, or LLM integration – practical production experience
6. Cloud & data platforms – Azure and Databricks fluency
7. Team leadership – experience leading small senior teams and managing supplier relationships
8. In-house ownership bias – proven track record reducing external dependency for critical IP
9. FCA regulated environment – judgement to maintain compliance without blocking velocity