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Agentic AI Engineer

Korn FerryLondon🇬🇧United KingdomPosted 17 Sept 2026

Quick Overview

Seniority
Mid Senior
Employment type
Temporary/Casual
Work mode
On Site
Location
London, United Kingdom
DatabricksGit

Job Description

Location: London - Hybrid, 3 days per week onsite
Contract: 12-month contract
Rate: Up to £575 per day inside IR35

Role Overview

We are looking for a hands-on Agentic AI Engineer to join a major financial services organisation in London.

You will design and implement agentic AI workflows that automate and accelerate software development activities, including coding, testing, quality assurance and continuous integration.

The role will involve translating business requirements into practical AI-driven engineering solutions that integrate with existing repositories, architecture and CI/CD pipelines. A key focus will be building safe, controllable and reusable AI workflows with appropriate validation, quality gates and human oversight.

Key Responsibilities

  • Design and build multi-step Agentic AI workflows across coding, code review, testing and defect resolution.
  • Develop connected AI pipelines capable of generating code, executing tests, analysing failures and iteratively refining implementations.
  • Assess existing repositories, architecture and technology stacks before implementing AI automation.
  • Integrate Agentic AI capabilities with Git-based development processes and CI/CD pipelines.
  • Embed validation controls, quality gates, evidence capture, safe stopping conditions and human-in-the-loop approval.
  • Package Agentic AI workflows so they can be reused across different teams and development environments.

Essential Experience

  • Strong hands-on engineering background within Software Engineering, SDET, Quality Engineering, Data Engineering, DevOps or Platform Engineering.
  • Proven practical experience with Agentic AI tools such as GitHub Copilot and/or Databricks Genie.
  • Experience designing multi-step AI workflows covering code generation, review, automated testing and iterative refinement.
  • Strong understanding of automated testing and shift-left quality practices.
  • Experience with Git, pull requests and CI/CD pipelines.
  • Ability to translate business problems into practical AI-driven technical solutions.
  • Experience implementing human-in-the-loop validation, safe failure handling and reusable automation patterns.

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