AI Product Manager

AI Product Manager

We are seeking a dynamic and strategic AI Product Manager to lead the successful delivery and lifecycle management of our enterprise AI use cases. This role sits at the intersection of product strategy, technology, agile delivery, and stakeholder engagement. The AI Product Manager will own both the implementation and long-term evolution of AI-powered products and tools, ensuring they are embedded seamlessly into the business and deliver measurable value.

You’ll be responsible for managing a portfolio of AI initiatives—from ideation through to deployment and scaling—while ensuring user-centric design, technical feasibility, governance, and KPIs are all aligned to strategic goals. Working closely with cross-functional teams including Data Science, Engineering, Operations, Compliance, and CX, you will define product visions, break them into actionable work, and ensure consistent delivery using agile methodologies.

This is a highly collaborative, hands-on role that requires a strong mix of product thinking, technical awareness, project leadership, and business communication skills.

Key Responsibilities

• Product Ownership & Strategy: Define and own the roadmap for multiple AI product use cases, from discovery through to production and post-launch support. Align product goals with wider business strategy and KPIs, ensuring every use case ties back to tangible impact. Evaluate and prioritize AI initiatives based on value, risk, feasibility, and stakeholder needs. Continuously improve AI product performance and user adoption based on feedback and analytics.
• Delivery & Agile Management: Translate business problems into detailed epics, features, and user stories in JIRA. Collaborate with developers, data scientists, MLOps engineers, and scrum masters to ensure smooth execution. Own the backlog: prioritise and groom regularly, ensuring clarity of acceptance criteria and dependencies. Track and report against delivery milestones and KPIs.
• Stakeholder & Change Management: Work across multiple business and technology teams to gather requirements, validate problems, and socialise solutions. Engage senior stakeholders and subject matter experts regularly to secure buy-in and ensure alignment. Run workshops, demos, and training sessions as needed to onboard users and gather feedback. Be the voice of the customer: ensure the AI products are usable, useful, and adopted.
• AI Governance & Risk Management: Partner with Legal, Risk, and Compliance to ensure AI products meet regulatory, ethical, and transparency requirements. Document model decisions, inputs, and known risks as part of AI governance best practice. Stay informed on emerging trends, risks, and frameworks in responsible AI.
• Knowledge Management & Documentation: Create and maintain structured documentation for AI products, including business context, workflows, known limitations, and user guides. Act as a point of contact for internal teams needing to understand how specific AI features or products work. Contribute to a shared knowledge base around AI use cases, including lessons learned and reusable components.

Key Use Cases You May Support

Depending on the evolving portfolio, you may lead or support initiatives such as:

• Automating summarisation of service cases or emails
• Knowledge search enhancements via LLMs integrated into service platforms.
• Email response generation for client servicing using fine-tuned models.
• Classification and tagging of support tickets or client queries.
• Generative AI knowledge assistants for internal operations teams.

Experience & Skills Required

Essential:

• Proven experience as a Product Manager, AI Delivery Manager, or Technical Product Owner.
• End-to-end product ownership of technology or data-driven solutions.
• Hands-on experience with Agile software development (JIRA, user stories, backlog management).
• Strong stakeholder engagement and communication skills across technical and non-technical audiences.
• Familiarity with common AI/ML concepts: NLP, classification, summarisation, generative AI.
• Ability to work across multiple priorities and drive alignment in ambiguous environments.
• Experience managing KPIs, dashboards, and impact tracking.

Desirable:

• Previous experience working with Data Science or MLOps teams.
• Exposure to prompt engineering or LLM-based products (e.g., GPT-4, Claude, Gemini).
• Familiarity with AI governance principles and regulatory compliance (e.g., EU AI Act, Responsible AI frameworks).
• Background in financial services or regulated industries.

Success Measures

You’ll be successful in this role if you:

• Consistently deliver AI use cases that are adopted and used by the business.
• Maintain strong stakeholder trust and clear communication channels.
• Translate technical capabilities into products that are usable, valuable, and compliant.
• Establish clear KPIs for every product you manage and use data to improve outcomes.
• Help your team reduce delivery risks by identifying unknowns early and making decisions swiftly.

Role Details

Title: AI Product Lead

Reports to: Head of AI Enablement

Location: Hybrid – London

Contract Type: Full-time

Salary: Competitive + bonus + benefits

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

Key skills/competency

• AI Product Management
• Agile Methodologies
• Stakeholder Engagement
• Natural Language Processing (NLP)
• Generative AI
• Data Science Collaboration
• Roadmap Development
• JIRA
• AI Governance
• Risk Management