Your new company

Hays has partnered with a long-standing public-sector organisation delivering large-scale, mission-led digital programs. Join a technology-forward organisation focused on responsibly introducing modern tools while operating under strict governance and privacy obligations.

Your new role

A long term contract leading the technical build and operational rollout of AI projects across the organisation. A practical AI engineering lead who contributes code, diagnoses production issues and drives end-to-end implementation across data and model workflows. Create and champion reusable architectural patterns and components that speed secure, repeatable AI rollouts in mixed legacy and cloud environments. Advise on applied GenAI approaches, retrieval-augmented pipelines, vector search, embeddings and copilot-style integrations with a focus on feasibility and risk. Convert technical trade-offs into concise guidance for senior stakeholders and take responsibility for architectural choices through to delivery. Partner with product owners, compliance, ICT and business groups to ensure solutions are responsible, usable and deliver clear operational benefit. Steer initiatives through governance checkpoints so work progresses from prototype to production while meeting lifecycle, security and regulatory needs. Work with business teams to phase delivery into pragmatic, high-value increments that mitigate risk and unlock longer-term change.

What you'll need to succeed

At least ten years’ experience in software or data engineering, including five or more years delivering AI/ML outcomes in enterprise settings. A proven ability to produce results within legacy-constrained and resource-limited environments while remaining pragmatic about scope. Strong hands-on capability in Python and contemporary agentic AI frameworks, paired with experience in cloud-native designs (Azure desirable). Practical expertise across data platforms such as data lakes, APIs and integration approaches, plus productionising models with monitoring, security and retraining workflows. A solid understanding of Responsible AI principles, privacy-by-design and compliance considerations relevant to public-sector contexts. Experience mentoring engineers and lifting capability by embedding DevOps/MLOps practices, automated testing and operational monitoring. Excellent communication and stakeholder skills with a history of building cross-functional ways of working.

What you'll get in return

A senior technical contract where you directly shape how AI is adopted across a large public program.
The opportunity to design and deliver ethical, operational AI solutions that produce measurable benefits for users.
A hybrid work arrangement combining remote flexibility with regular in-person collaboration.
A chance to lead capability uplift, mentor technical teams and institutionalise modern engineering practices.
Meaningful exposure to complex, high-impact problems that enhance your leadership record in regulated environments.