At a Glance
- Tasks: Lead the strategy and design of AI telemetry systems to monitor and optimise performance.
- Company: Join LSEG, a leader in financial technology with a commitment to innovation.
- Benefits: Enjoy healthcare, retirement planning, paid volunteering days, and well-being initiatives.
- Other info: Collaborate across teams to drive insights and improve AI system reliability.
- Why this job: Make a real impact on AI governance and user experience in a dynamic environment.
- Qualifications: Experience in product management with a focus on observability and data platforms.
The predicted salary is between 80000 - 100000 £ 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 analyze how AI models, MCPs, and AI-enabled features behave across all LSEG products. This role is responsible for defining how we collect, structure, analyze 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
- 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, 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 and external stakeholders.
Benefits
LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and well-being initiatives.
Equal Opportunity Statement
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.
Senior Product Manager for AI Observability employer: Dormont Manufacturing Co
LSEG is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Senior Product Manager – AI Observability role. With a strong focus on employee growth, we offer tailored benefits such as healthcare, retirement planning, and well-being initiatives, ensuring our team members thrive both personally and professionally. Located in a dynamic environment, our commitment to diversity and inclusion, alongside opportunities to influence cutting-edge AI governance and performance, makes LSEG a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Manager for AI Observability
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We think you need these skills to ace Senior Product Manager for AI Observability
Some tips for your application 🫡
Show Off Your Product Passion:When applying for a product management role like Senior Product Manager for AI Observability, let your passion for developing products shine through in your cover letter. Share specific examples of products you've managed, how you solved user needs, and any successful outcomes you've achieved. This is your chance to showcase your understanding of the product lifecycle!
Highlight Your Cross-Functional Skills:Product management isn't just about understanding the product; it’s about collaborating with different teams! Make sure to emphasise your experience working with developers, designers, and marketers. Use your CV to showcase your ability to bridge gaps between these areas, and include relevant experiences that demonstrate your communication and leadership skills!
Include Your Metrics and Achievements:In a full-time product management application, data speaks volumes! Quantify your achievements wherever possible. Did you increase user retention by a certain percentage? Launch a product ahead of schedule? Include these metrics in your CV to paint a picture of your impact and effectiveness in previous roles.
Tailor Your CV to the Role:Make sure your CV is tailored for the Senior Product Manager for AI Observability position at Dormont Manufacturing Co. Use keywords from the job description and ensure your relevant experiences are front and centre. Highlight any certifications or relevant training you’ve completed that will make you stand out as a strong candidate for the role. And remember, we’re excited to see your application on our website!
How to prepare for a job interview at Dormont Manufacturing Co
✨Understand the Product Life Cycle
As a product management candidate, we need to get our head around the complete product life cycle. Be prepared to discuss real-world examples of how you’ve managed product development from ideation to launch. Bring specific insights on tools like JIRA or Trello that can help streamline these processes.
✨Showcase Your Cross-Functional Skills
Product management is all about collaboration. We should be ready to highlight how we’ve worked across teams—think marketing, engineering, and design. Prepare to discuss scenarios where you had to mediate differing opinions and how you got everyone on board with a shared vision.
✨Prepare for Case Studies
In a full-time role, we can expect to encounter case study questions during our interviews. Practise solving hypothetical product problems on the spot, such as prioritising features for a new app or improving user engagement metrics. This will show our analytical thinking and decision-making skills.
✨Know Your Metrics
Let’s face it, numbers are our best friends in product management. We should prepare to discuss key performance indicators (KPIs) and how we've used analytics to inform product decisions. Dive into examples where data has driven our strategy for improvements or justified product changes.
