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About the Role
We are seeking a hands-on Principal AI Engineer to act as the technical right hand for the Automation & AI Practice, accelerating the Colleague AI agenda. This pivotal role will transition the organisation from isolated AI experiments to a fully resourced, governed, and scalable AI delivery capability. You will seed in-house expertise to reduce vendor dependency, mitigate key person risk, and govern shadow AI usage across the business.
Responsibilities
- Provide hands-on technical leadership across Colleague AI initiatives including Sierra PoC and Claude roll-out, owning architecture and design.
- Drive the build of agentic AI solutions for Tribeless colleagues.
- Consult on the broader Colleague AI backlog (complaint triage, helpdesk assistant, inbox routing, QA/QC), ensuring solutions are fit for purpose, secure, low risk, and cost-efficient amid consumption-based AI pricing.
- Define and embed AI engineering standards, reference architectures, and reusable patterns, collaborating with infrastructure teams to govern shadow AI usage.
- Lead AI literacy and enablement across Digital and the wider business.
- Mentor and uplift the Automation Practice team to diffuse AI capability and support transition to a permanent in-house AI Engineering Manager.
- Represent the Automation & AI Practice in cross-functional forums, translating AI strategy into delivery roadmaps and measurable outcomes.
Requirements
- Deep, hands-on technical leadership experience at Principal/Lead level.
- Strong expertise in Generative AI, LLMs, agentic architectures, and multi-agent systems with proven production delivery in regulated environments (FS preferred).
- Proven experience building agentic solutions using Microsoft Copilot Studio/Foundry, AWS Bedrock/AgentCore, and frameworks such as LangChain, LangGraph, CrewAI, Strands.
- Comfortable across Microsoft and AWS cloud ecosystems, including LLM gateway/Bedrock patterns, data residency, SSO/OIDC federation, and cost controls.
- Experience with Claude/Anthropic, OpenAI, Microsoft Copilot families, including MCP, connectors, skills, and trade-offs.
- Strong understanding of AI testing disciplines (accuracy, hallucination, bias, prompt evaluations) and AI governance/risk (DPIA, data classification, FCA considerations).
- Excellent stakeholder management skills, able to engage from board-level to engineer-level.
- Mentorship and capability-building mindset to strengthen the team and avoid key-person dependency.
Skills
- Generative AI
- LLMs
- Agentic architectures
- Multi-agent systems
- Microsoft Copilot Studio/Foundry
- AWS Bedrock/AgentCore
- LangChain
- LangGraph
- CrewAI
- Strands
- Microsoft cloud ecosystems
- AWS cloud ecosystems
- LLM gateway/Bedrock patterns
- Data residency
- SSO/OIDC federation
- Cost controls
- Claude/Anthropic
- OpenAI
- Microsoft Copilot families
- MCP
- Connectors
- Skills
- AI testing disciplines
- AI governance/risk
- Stakeholder management
- Mentorship
- Capability-building
Location
- Central London
Work Type
- Hybrid
- Full Time
Experience Level
- Principal
- Lead
Salary/Compensations
- Very competitive day rate, Inside IR35
Benefits
- Enhancing client NPS
- Helpdesk demand deflection
- Colleague efficiencies
- Boosting colleague productivity
- Improving AI literacy and adoption
- Accelerating solution time to market
- Reducing digital dependency
- Driving ongoing colleague productivity gains