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
*Lifecycle ownership of core investment and operations systems
*Application portfolio including architecture, technical roadmap, framework modernization
*Decommissioning legacy components and driving technical evolution
AI-Augmented Delivery
*Drive adoption of Claude Code , agentic pipelines, and AI-generated testing across the development lifecycle
*Productionize existing PoCs (unit test generation, codebase documentation, ADO-to-GitHub automation)
*Build AI-native delivery model reducing external supplier dependency
MCP & Integration Architecture
*Build MCP connector layer exposing proprietary systems to firm’s AI estate
*Implement governance, audit trails, and access controls
*Enable secure, governed AI integration with core platforms
Team & Supply Model
*Lead small senior in-house engineering squad augmented by selected contractors
*Set engineering standards, code review culture, and delivery cadence
*Reduce dependency on external development suppliers through AI-augmented in-house capability
Governance & Audit Readiness
*Ensure institutional investor scrutiny standards met
*AI code provenance, container hardening, change control, full audit trails
*FCA regulated environment compliance without slowing delivery
We’re Looking For
An engineering leader who has done the work, not just managed it.
Essential:
*Strong track record building and running proprietary applications in financial services
*Deep .NET background with modernization programme experience
*Multi-language fluency - .NET, Python, TypeScript, SQL
*Hands-on AI tooling experience - Claude Code, Cursor, or equivalent AI-native development tools with clear POV on effective use
*MCP, agent frameworks, or LLM integration - practical production experience
*Cloud & data platforms - Azure and Databricks fluency
*Team leadership - experience leading small senior teams and managing supplier relationships
*In-house ownership bias - proven track record reducing external dependency for critical IP
*FCA regulated environment - judgement to maintain compliance without blocking velocity