Level

LSEG

Senior Product Manager for AI Observability

AI in this role

ai-evaluationai-safety

Role Profile 

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. 

This role is responsible for defining how we collect, structure, analyse and act on AI-specific telemetry signals—including prompt patterns, model performance, MCP call usage, latency, error conditions, cost metrics, user behaviour signals, and system reliability. 

You will develop a telemetry foundation that supports: 

  • AI governance & risk 

  • model performance tracking 

  • cost efficiency 

  • user experience optimisation 

  • operational reliability 

  • auditability 

  • and the long-term evolution of our AI platform. 

Key Responsibilities & Accountabilities 

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. 

 

Skills & Competencies 

Required 

  • 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

London Stock Exchange Group (LSEG) Information:

Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.

LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.

If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.

How we rate this

Senior Product Manager for AI Observability at LSEG rates 76 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI EvaluationAI Safety

Questions you could be asked

  1. How do you decide that one model's output is better than another's for a given task?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI Evaluation and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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