Agentic AI Engineer
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-10-15
Listing for:
Henderson Scott
Full Time
position Listed on 2026-10-15
Job specializations:
-
Software Development
AI Engineer (Applied/Software), AI QA / Validation Engineer
Job Description & How to Apply Below
Agentic AI Engineer / AI Adoption Specialist
- Location:
Remote (UK-based) - Contract Length: 12 Months
- Rate:
Competitive (Inside IR35) - Security Clearance:
Active SC ESSENTIAL
Job Description We are looking for an experienced Agentic AI Engineer for an initial 12-month contract to drive the adoption and implementation of cutting-edge AI engineering practices across large-scale delivery environments. In this role, you will champion hands‑on agentic AI workflows, mentor engineering teams, and establish enterprise standards for AI‑assisted software development, spanning the entire Software Development Life Cycle (SDLC).
Key Responsibilities- Agentic AI Engineering:
Build and run agent workflows, handle model selection, prompt/harness engineering, agent-tool integration, and manage reusable skills and instructions. - SDLC Integration:
Apply AI across the full software lifecycle, including test generation, code review augmentation, documentation, legacy comprehension, and modernisation. - AI Tooling & Ecosystem:
Leverage and integrate AI coding and agent tooling such as Claude Code, Git Hub Copilot, Codex, Kiro, and MCP server development. - Standards & Governance:
Define standards, guardrails, and engineering practices adopted across multiple teams, with demonstrable evidence of successful adoption. - Stakeholder Influence:
Influence without formal authority across organisational and team boundaries, engaging effectively with technology providers and suppliers. - Community &
Coaching:
Provide targeted training, coaching, and run champions networks to build a self‑sustaining community of practice.
- Hands‑on AI Engineering:
Proven experience building agentic workflows, prompt/harness engineering, and reusable instructions. - SDLC AI Application:
Demonstrated success applying AI to testing, code review, documentation, and legacy system modernisation. - Tool Exposure:
Direct experience with modern AI coding assistants and agent tooling (e.g., Claude Code, Git Hub Copilot, MCP servers). - Culture & Governance:
Track record of defining cross‑team engineering standards and driving wide‑scale adoption. - Collaboration & Leadership:
Strong influencing skills without formal authority, coupled with experience in coaching and running champions networks. - Security Clearance:
Must hold an active SC clearance.
- Background in software engineering for large-scale production systems, sufficient to seamlessly embed within technical delivery teams.
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