Senior Product Manager, AI

About the role

LSEG is looking for a hands-on AI Product Co-Developer to join its team building production-grade agentic AI systems for complex, data-intensive environments. This is a hybrid role combining product thinking and engineering depth: you will define what gets built and actively build it, working across the full lifecycle from discovery and requirements through to deployment and iteration.

Key responsibilities

• Contribute to the full AI product lifecycle: discovery, requirements definition, development, testing and deployment.
• Design, build and iterate on LLM-powered agentic workflows, applying sound orchestration patterns and tool-use design.
• Translate business and user needs into clear product requirements and agent configurations.
• Define and monitor product performance metrics and acceptance criteria for AI outputs in production, covering accuracy, latency, cost and auditability.
• Manage the post-launch lifecycle: track performance, gather user feedback and contribute to model or feature refresh cycles.
• Contribute to system optimisation across performance, cost and operational constraints.
• Work with governance teams to ensure AI outputs meet quality, compliance and interoperability standards.
• Keep up with the evolving AI landscape and turn relevant developments into product opportunities.
• Engage with internal stakeholders and cross-functional teams, support demos and presentations of prototypes, and share expertise in AI product design and agentic workflows.

Required profile

• 7+ years of experience spanning software or ML engineering and product development, or a closely related combination.
• Demonstrated hands-on experience building with LLMs and/or agentic frameworks; shipped products or features preferred over academic work.
• Working knowledge of how LLMs and agentic systems behave in production, including tool use, prompt design, orchestration patterns, output variability and failure modes.
• Ability to write clear product requirements and define, review and challenge technical specifications without needing engineering support.
• Solid Python skills and familiarity with APIs, data pipelines and cloud infrastructure.
• Experience with real-time or near-real-time data systems, with a sense of latency, throughput and cost trade-offs.
• Familiarity with responsible AI principles, including data quality, model monitoring and bias considerations in regulated environments.
• Comfortable working across technical and commercial stakeholders.
• BA, BS or Master's degree in Computer Science, Engineering, Mathematics or a related field, or equivalent practical experience.