Senior Product Manager for AI Observability

Overview

As Senior Product Manager for AI Observability, you will shape the telemetry strategy and build the platform that monitors AI model behavior across LSEG products. You’ll define standardized telemetry and partner with engineering to ensure scalable, compliant instrumentation. The role drives governance-focused insights, AI cost efficiency, and reliable, auditable AI experiences. You will collaborate across divisions to translate telemetry into product decisions and roadmap priorities.

Pay / Benefits

• Healthcare
• Retirement planning
• Paid volunteering days
• Wellbeing initiatives

Responsibilities

• Define the end-to-end telemetry vision and roadmap for LLMs, MCPs, vector stores, embeddings, inference layers, and AI-powered experiences
• Standardize telemetry schema to capture prompts, tool calls, model responses, durations, errors, confidence signals, and quality indicators
• Partner with platform engineering to ensure instrumentation is consistent, scalable and compliant
• Identify key signals for quality, latency, cost, MCP usage, user workflows, failures, guardrails and safety events
• Define retention rules, PII considerations, anonymisation and usage policies with AI Governance and Compliance
• Own dashboards, monitoring tools, model comparison views, anomaly alerts, and performance scorecards
• Enable product and engineering teams to self-serve insights about AI model behavior and MCP interactions
• Build pipelines for real-time and batch analytics with engineering
• Collaborate with product owners across LSEG to instrument AI features consistently
• Drive cost optimisation and ROI by identifying inefficiencies in model and MCP usage
• Surface workflow-level insights to inform product roadmaps and customer experience improvements
• Define and maintain AI telemetry standards and best practices across divisions
• Contribute to AI governance initiatives with data-driven insights on model behavior and user impact
• Ensure telemetry supports auditability, compliance and explainability

Key requirements

• Experience in product management with strong foundation in observability, telemetry, data platforms, monitoring, or SRE/DevOps-driven products
• Understanding of LLMs, embeddings, vector search, MCP tools, and AI inference workflows
• Deep familiarity with logging, tracing, metrics, and event-based telemetry systems
• Ability to define data schemas, signal taxonomies, aggregation strategies and data contracts
• Strong analytical skills and ability to derive insights from large-scale system telemetry
• Experience working with senior engineering, data science, risk and governance stakeholders

• Cross-functional collaboration
• Analytical mindset
• Strong communication skills
• Observability and telemetry
• Data platforms and pipelines
• Logging, tracing, metrics, event-based telemetry

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