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- Tasks: Lead the strategy and design of AI telemetry systems for monitoring and analysis.
- Company: Join LSEG, a leader in AI innovation with a commitment to diversity.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on responsible AI and governance.
- Why this job: Shape the future of AI observability and make a real impact across products.
- Qualifications: Experience in product management and a strong understanding of AI and telemetry.
The predicted salary is between 80000 - 100000 ÂŁ per year.
As part of the LSEG AI, we are hiring a Senior Product Manager – AI Observability to own the strategy, design and rollout of telemetry systems that monitor, measure and analyse how AI models, MCPs, and AI‑enabled features behave across all LSEG products.
Responsibilities
- Telemetry & Observability Strategy
- Define the end‑to‑end telemetry vision and roadmap for LLMs, MCPs, vector stores, embeddings, inference layers and AI‑powered user experiences.
- Establish a standardised telemetry schema for capturing prompts, tool calls, model responses, durations, errors, confidence signals, and quality indicators across business lines.
- Partner with platform engineering to ensure instrumentation is consistent, scalable and compliant.
- Signal Design & Data Architecture
- Identify key signals required for quality & reliability, latency & throughput, cost tracking & optimisation, MCP usage patterns, user workflow insights, failure pattern detection, guardrail and safety event monitoring.
- Define retention rules, PII considerations, anonymisation and usage policies in partnership with AI Governance and Compliance.
- Platform & Tooling
- Own requirements for dashboards, monitoring tools, model comparison views, anomaly detection alerts, and performance scorecards.
- Design systems that allow product and engineering teams to self‑serve insights about AI model behavior and MCP interactions.
- Partner with engineering to build pipelines that support real‑time and batch analytics.
- Cross‑Functional Collaboration
- Collaborate with product owners across LSEG to instrument their AI features consistently.
- Partner with AI Evaluation PM (previous role), Model Risk, GSSR, Legal and Compliance to align telemetry with governance frameworks.
- Work closely with Engineering and SRE teams to drive observability improvements and reliability engineering for AI systems.
- Optimisation & Insights
- Identify cost inefficiencies across model and MCP usage, and drive recommendations to improve ROI.
- Surface workflow‑level insights on how customers use AI features—informing product roadmaps.
- Partner with product leaders across divisions to understand how telemetry can improve customer experience, reliability and performance.
- Governance & Standards
- Define and maintain AI telemetry standards and best practices across all LSEG divisions.
- Contribute to LSEG’s AI governance and Responsible AI initiatives by providing data‑driven insights on model behavior and user impact.
- Ensure telemetry systems support auditability, compliance and explainability requirements.
Required Skills & Competencies
- Experience in product management with a 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.
Preferred
- Exposure to financial data, analytics systems and enterprise‑scale data workflows.
- Familiarity with BI tools, metrics stores, distributed tracing and monitoring stacks.
- Understanding of cloud infrastructure, serverless runtimes, API gateways and model hosting architectures.
- Ability to drive cross‑functional alignment and establish group‑wide standards.
Measures of Success
- Platform Reliability & Performance
- Reduction in AI system error rates, latency spikes and operational incidents.
- Stability and transparency of MCP usage across product lines.
- Quality and coverage of telemetry signals across all AI‑enabled products.
- Insight Generation & Adoption
- Adoption of telemetry dashboards and self‑service tools across divisions.
- Number of identified and resolved model or MCP reliability issues driven by telemetry.
- Level of insight generated to influence product prioritisation and AI model choices.
- Operational Efficiency & Cost
- Improved cost transparency and cost‑saving impact via telemetry‑driven optimisation.
- Reduction in unnecessary model invocation or inefficient tool usage.
- Governance & Compliance
- Contribution to Responsible AI frameworks through robust, auditable telemetry.
- Improved explainability and traceability of AI features for internal/external stakeholders.
Career Stage
Manager
Equal Employment Opportunity Statement
We are proud to be an equal opportunities employer. We do not discriminate on the basis of any protected characteristic and we accommodate religious practices, mental health or physical disability needs. Candidates are required to read the privacy notice regarding personal information.
Senior Product Manager for AI Observability in London employer: LSEG
Contact Detail:
LSEG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Product Manager for AI Observability in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Prepare for interviews by researching the company and its products. Knowing their AI observability strategy inside out will show you're genuinely interested and ready to contribute.
✨Tip Number 3
Practice your pitch! Be ready to explain how your experience aligns with the role of Senior Product Manager. Highlight your skills in telemetry and observability clearly.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Senior Product Manager for AI Observability in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in product management, especially in observability and telemetry. We want to see how your skills align with our needs for the Senior Product Manager role.
Showcase Relevant Experience: When detailing your past roles, focus on your achievements related to AI systems, data platforms, and cross-functional collaboration. We love seeing concrete examples of how you've driven improvements in reliability and performance.
Be Clear and Concise: Keep your application straightforward and to the point. Use bullet points where possible to make it easy for us to see your key qualifications and experiences at a glance. We appreciate clarity!
Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at LSEG
✨Know Your Telemetry Inside Out
Make sure you understand the ins and outs of telemetry systems, especially in relation to AI models and observability. Brush up on key concepts like logging, tracing, and metrics, as well as how they apply to LSEG's products.
✨Showcase Your Cross-Functional Collaboration Skills
Be prepared to discuss your experience working with various teams, such as engineering, data science, and compliance. Highlight specific examples where you've successfully driven alignment and collaboration across departments.
✨Demonstrate Analytical Prowess
Expect questions that test your analytical skills. Be ready to explain how you've derived insights from large-scale telemetry data in the past and how those insights influenced product decisions or improvements.
✨Familiarise Yourself with Financial Data Workflows
Since the role involves exposure to financial data and analytics systems, it’s a good idea to brush up on your knowledge in this area. Understand how telemetry can improve ROI and customer experience in financial contexts.