Principal Engineer – AI Productivity Lab

Overview

As Principal Engineer for the AI Productivity Lab, you will lead the engineering of domain-specific agents and tooling that accelerate AI-driven employee productivity. You work within the Data & AI Team to shape and deliver practical AI capabilities aligned with business procedures, enabling safe, repeatable automation. You will partner with business leaders to embed agents into SOPs and measure impact, turning ideas into MVPs and scalable solutions. This role offers high visibility in shaping how the organisation harnesses AI to improve workflows and outcomes. You’ll join a mission-driven team that values innovation, collaboration, and responsible AI adoption.

Pay / Benefits

• Generous pension contribution up to 15%
• Annual performance-related bonus
• Share schemes including free shares
• Discounted shopping benefits
• 30 days’ holiday plus bank holidays
• Wellbeing initiatives and parental leave policies

Responsibilities

• Lead coworking solutions (agents, tools, automations) from prototype to MVP
• Design and build reusable capabilities for the lab platform and repository (skills, tools, SOP assets)
• Apply agentic coding and coworking tools to evaluate options and accelerate delivery
• Partner with stakeholders to shape use cases, embed solutions into SOPs, and measure outcomes
• Coach and mentor engineers, conduct code reviews, and align technical direction with senior stakeholders

Key requirements

• Proven experience delivering technology solutions to business areas in complex production environments with ownership of outcomes
• Extensive knowledge of solutions architecture, software engineering and business process automation
• Strong hands-on experience with agentic coding and/or coworking technology and ecosystems (Claude Code, Cowork, OpenClaw, GitHub Copilot)
• Strong understanding of operational processes and risk management (Financial Services preferred)
• Ability to influence stakeholders and guide teams through ambiguity into MVPs

• Influencing stakeholders
• Translating productivity opportunities into clear technical direction
• Mentoring and coaching engineers
• Agentic coding
• Coworking technology and ecosystem expertise (Claude Code, Cowork, OpenClaw, GitHub Copilot)
• Solutions architecture

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