Senior Associate/Assistant Vice President, AI Product Manager

What you'll do

• Own the end-to-end lifecycle of assigned AI products, including discovery, opportunity sizing, solution design, prioritisation, launch, adoption tracking and iteration, with accountability for measurable business results.
• Set product vision and strategy for AI use cases across investment, portfolio monitoring, research and operations workflows, turning senior stakeholder intent into sequenced roadmaps.
• Make design decisions on AI systems, such as choosing between RAG, fine-tuning or prompt engineering, structuring agent workflows for reliability, adding human-in-the-loop checkpoints and designing evaluation frameworks.
• Run product discovery by researching with investment professionals, observing real workflows, analysing pain points and turning findings into prioritised backlogs.
• Own the evaluation strategy, defining success metrics, building evaluation datasets and maintaining benchmarks across model and prompt versions.
• Translate implicit business needs from investment and operations teams into technically actionable AI product specifications covering data, model capability, integration points and error tolerances.
• Maintain a product requirements framework for AI systems, including system prompts, agent behaviour specs, tool definitions, API contracts, evaluation rubrics, guardrails and feedback mechanisms.
• Act as the main interface between business stakeholders and engineering, managing expectations, explaining probabilistic outputs to non-technical users and reporting performance transparently.
• Build and maintain a business case framework linking product metrics like usage, accuracy and latency to business value metrics such as time saved, decision quality and risk reduced.
• Lead cross-functional delivery squads of AI engineers, data engineers, UX designers and domain specialists, managing dependencies and escalating blockers with context and proposed solutions.
• Partner with the AI Security & Governance Lead to embed governance and compliance throughout product development rather than at launch.
• Work with the AI Fluency and Change Management team on adoption programmes, including user education, rollout strategy and feedback loops.
• Engage the platform engineering team to feed product requirements into platform planning so common patterns become reusable components.
• Design and deliver enablement programmes that help non-technical employees build low-code, no-code and AI-assisted solutions on approved enter