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AI Product Lead

Job in Southampton, Hampshire County, SO15, England, UK
Listing for: Quilter
Full Time position
Listed on 2026-07-11
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Evaluation, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 90000 - 150000 GBP Yearly GBP 90000.00 150000.00 YEAR
Job Description & How to Apply Below

About The Business

Quilter plc is a leading wealth management business, helping to enable brighter financial futures for every generation. The company oversees £141.9 billion in customer investments (as at end March 2026). It offers financial advice, investment platforms, multi‑asset investment solutions, discretionary fund management, and caters to two segments:
Affluent and High Net Worth. Affluent includes the financial planning business, Quilter Financial Planning, the Quilter Investment Platform and Quilter Investors. High Net Worth covers the discretionary fund management business, Quilter Cheviot, together with Quilter Cheviot Financial Planning, offering a highly personalised service to private clients, charities, trustees, and professional partners across the UK, Ireland and Channel Islands.

Quilter continuously modernises, becomes more customer‑centric, and welcomes bold ideas and innovation to remain ahead of the industry.

About

The Role

The AI Product Lead sits within the Chief Data Office, reporting directly to the Head of AI. The role is permanent, based in London or Southampton, and operates at Level 5. The successful candidate will shape, deliver, and govern AI products across Quilter, ensuring alignment with business priorities, regulatory expectations, and responsible AI standards.

Responsibilities
  • AI Product Strategy & Roadmap – Define and own the AI product vision, roadmap, and prioritisation of use cases aligned to business value and strategic objectives. Translate business needs into clear AI problem statements and delivery plans.
  • Project & Delivery Management – Lead end‑to‑end delivery of AI products using agile methodologies and manage milestones, dependencies, and risks to ensure timely, high‑quality outcomes.
  • Value Realisation & Adoption – Track product performance, business impact, and user adoption. Ensure AI solutions deliver measurable outcomes and evolve based on feedback and metrics.
  • AI Governance & Responsible AI Alignment – Collaborate closely with AI Governance, Risk, Legal, and Compliance teams to ensure all AI products adhere to Quilter’s AI governance framework.
  • Model Risk & Evaluation Oversight – Apply robust evaluation frameworks across ML and GenAI solutions, including accuracy, fairness, bias, explainability, and hallucination monitoring. Support model validation prior to production deployment.
  • Stakeholder Engagement & Leadership – Build strong collaborative relationships across business units, technology, and senior stakeholders. Act as a trusted advisor, ensuring alignment, transparency, and effective communication throughout the product lifecycle.
  • Cross‑Functional Collaboration – Work closely with AI Scientists, Engineers, Product Owners, and business SMEs to ensure seamless delivery of AI solutions across the AI development lifecycle.
  • Leadership & Team Contribution – Lead and mentor team members where appropriate, fostering a high‑performance, collaborative, and delivery‑focused culture.
Third‑Party Vendor Assessment & Due Diligence

Provide technical and product leadership input into the evaluation of AI vendors and external solutions. Support due diligence, risk assessment, and alignment to Quilter’s standards for secure and responsible AI adoption.

Qualifications
  • Bachelor’s degree in a relevant field (e.g., Computer Science, Data Science, Engineering, Business, or similar).
  • Advanced degree (MSc/PhD in AI, Data Science, or related field) is advantageous but not required.
  • Certifications in AI/ML, Product Management, or Agile Delivery (e.g., Scrum, SAFe) are advantageous.
Knowledge
  • Strong understanding of Machine Learning, Generative AI, and LLM‑based solutions.
  • Knowledge of AI product lifecycle and delivery frameworks, including agile methodologies.
  • Solid understanding of AI governance frameworks, model risk management, and regulatory requirements (GDPR, EU AI Act, FCA guidance).
  • Awareness of AI/ML evaluation techniques and performance measurement.
  • Understanding of third‑party AI ecosystems and vendor integration approaches.
Experience
  • Proven experience in AI Product Management, AI Delivery Lead, or similar roles.
  • Demonstrated success delivering AI/ML or GenAI products…
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