Product Manager (Artificial Intelligence)

London Stock Exchange; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

London Stock Exchange is seeking a hands-on AI Product Co-Developer to join our team building production-grade agentic AI systems for data-intensive environments.

This hybrid role sits at the intersection of product thinking and engineering depth, defining what gets built and actively building it from discovery through deployment and iteration.

Qualifications

• 5+ years of software or ML engineering and product development experience.
• Solid Python skills and familiarity with APIs, data pipelines and cloud infra.
• Experience building with LLMs and agentic frameworks; shipped products preferred.
• Ability to translate product decisions for engineering and client audiences.

Responsibilities

• Define and monitor product performance metrics for AI outputs in production.
• Translate business and user needs into clear product requirements and agent configurations.
• Design, build, and iterate on LLM-powered agentic workflows for complex use cases.
• Collaborate with governance teams to ensure AI outputs meet standards.

Skills

LLM experience

Product ownership

Python

APIs

Data pipelines

Cloud infrastructure

Stakeholder communication

Latency awareness

Agentic frameworks

Tool-use design

Education

BA/BS in CS/Engineering/Math or related field

Tools

Agentic frameworks

LLM tooling

Workflow orchestration

Job description

• We are looking for a hands-on AI Product Co-Developer to join our team building production-grade agentic AI systems for complex, data-intensive environments
• This is a hybrid role sitting at the intersection of product thinking and engineering depth - you will both define what gets built and actively build it, working across the full lifecycle from discovery and requirements through to deployment and iteration
• Contribute to the full AI product lifecycle: discovery, requirements definition, development, testing, and deployment
• Design, build, and iterate on LLM-powered agentic workflows for complex, data-intensive use cases, applying sound orchestration patterns and tool-use design
• Translate business and user needs into clear, actionable 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 product lifecycle: track performance, gather user feedback, and contribute to model or feature refresh cycles
• Contribute to system optimisation across performance, cost, and operational constraints
• Collaborate with governance teams to ensure AI outputs meet internal quality, compliance, and interoperability standards
• Maintain a forward-looking view on the evolving AI landscape - including model capabilities, agentic frameworks, and emerging protocol standards - and translate relevant developments into product opportunities
• Engage with internal stakeholders and cross-functional teams to support successful delivery of AI capabilities
• Support demos and presentations of prototypes and new capabilities to internal and external audiences
• Build and share expertise in AI product design and agentic workflows across engineering, product, and domain teams

• Experience evaluating and testing AI outputs - defining acceptance criteria, identifying edge cases, and working with engineering teams to resolve model or integration issues
• Comfortable working across technical and commercial stakeholders - able to translate product decisions clearly for engineering teams and client-facing audiences alike
• Demonstrated hands-on experience building with LLMs and/or agentic frameworks - shipped products or features preferred over academic work
• Working knowledge of how large language models and agentic systems behave in production - including tool use, prompt design, orchestration patterns, output variability, and failure modes
• BA, BS, or Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience
• Experience with real-time or near-real-time data systems, with a natural sensitivity to latency, throughput, and cost trade-offs
• Exposure to AI partner platforms or ecosystems in a product, technical, or commercial capacity is an advantage
• Ability to write clear product requirements and define, review, and challenge technical specifications without requiring engineering support
• 5+ years of experience spanning software or ML engineering and product development, or a closely related combination - we value technical depth and product ownership in equal measure
• Familiarity with responsible AI principles - including data quality, model performance monitoring, and bias considerations - and their implications for product design in regulated environments
• Solid Python skills and familiarity with APIs, data pipelines, and cloud infrastructure