We're looking for an Agentic AI Engineer to join our team. In this role, you will design and implement agentic AI workflows that automate and accelerate software development activities, including coding, testing, quality assurance, and continuous integration.
You will translate business requirements into practical AI-driven engineering solutions integrated with repositories, architecture, and CI/CD pipelines.
The position involves building safe, controllable, and reusable AI patterns, ensuring proper validation, quality gates, and human oversight.
Responsibilities
- Translate business requirements into agentic AI workflows across coding, review, testing, and defect resolution
- Build connected AI-driven pipelines that can develop code, execute tests, analyse failures, and refine implementations iteratively
- Assess existing repository, architecture, and technology stack before proposing automation solutions
- Embed validation controls, quality gates, evidence capture, safe stopping conditions, and human approval checkpoints in solutions
- Package and integrate agentic AI workflows for reuse across teams and development environments
- Ensure measurable outcomes aligned with quality, security, and regulatory compliance
- Collaborate with engineering, QA, and DevOps teams to scale AI-driven capabilities across the organisation
- Support continuous improvement and responsible AI practices
Requirements (Must Have Skills)
- Strong hands-on background in software engineering, SDET, quality engineering, data engineering, DevOps, or platform engineering
- Proven experience using agentic AI tools such as GitHub Copilot and/or Databricks Genie
- Expertise in multi-step AI workflows for the development lifecycle: code generation, review, testing, and iterative refinement
- Proficiency in automated testing, shift-left quality practices, Git-based workflows, pull requests, and CI/CD
- Ability to translate business problems into technical AI solutions with measurable control points
- Experience embedding human-in-the-loop validation, safe failure handling, and reusable automation patterns
Nice to Have Skills
- Experience creating custom Copilot agents or repository-aware AI prompts
- Familiarity with Databricks workflows, notebooks, pipelines, and data-quality engineering
- Knowledge of AI agent evaluation, regression testing, and performance benchmarking
- Exposure to static analysis, security testing, observability solutions, and responsible AI governance
- Experience scaling AI engineering capabilities across large programs or multiple teams
Rate:
Not specified
Location:
London
IR35 Status:
Inside
Remote Status:
Hybrid
Industry:
AI & Machine Learning
Seniority Level:
Not Specified