AI Product Manager: Generative AI & ML Solutions

LexisNexis Risk Solutions; Greater London; Sur place; GBP 70 000 - 110 000; Plein temps

Résumé du poste

LexisNexis Risk Solutions is seeking a Product Manager to own AI-powered product capabilities and drive delivery from discovery to launch and adoption. You will translate customer needs and business objectives into actionable requirements, collaborating with Engineering, Data Science, UX, and business teams.

You will define priorities, manage backlogs, and measure adoption using clear metrics, ensuring privacy, reliability, and security in AI implementations.

Qualifications

• Experience owning product features or customer-facing software products.
• Experience with Agile product ownership, backlog management, sprint planning and product discovery.
• Strong analytical skills and ability to prioritize competing customer, business and technical requirements.
• Experience delivering AI-powered products (ML, Generative AI, intelligent automation, conversational AI).
• Ability to collaborate with Engineering, Data Science and UX teams to translate customer needs into requirements.

Responsabilités

• Define, refine, and prioritize requirements for AI-powered product capabilities and workflows.
• Partner with Engineering and Data Science teams to operationalize AI solutions.
• Manage product backlogs, write user stories, define acceptance criteria, and ensure delivery aligns with objectives.
• Participate in discovery activities including customer interviews, prototype validation, experimentation, and solution evaluation.
• Establish and track success metrics to measure product adoption, effectiveness, quality, and customer value.

Connaissances

Product management

Agile delivery

Cross-functional collaboration

Analytical thinking

AI product delivery

Description du poste

LexisNexis Risk Solutions is seeking a Product Manager to own AI-powered product capabilities and drive delivery from discovery to launch and adoption. You will translate customer needs and business objectives into actionable requirements, collaborating with Engineering, Data Science, UX, and business teams.

You will define priorities, manage backlogs, and measure adoption using clear metrics, ensuring privacy, reliability, and security in AI implementations.