Product Manager, Agent Enablement
Meta London, England, United Kingdom
Software Development · 10,001+ employees
About the role
Lead the product vision and strategy for conversational AI agents, driving them from prototype to production at scale. Collaborate with cross-functional teams to define roadmaps, establish evaluation frameworks, and ensure continuous improvement of AI systems.
What they look for
Requirements
Requires 8+ years of industry experience with at least 3 years in Product Management, specifically in shipping live agentic systems. Candidates must demonstrate strong technical leadership, data-driven decision-making, and the ability to influence cross-functional teams.
Full description
Meta Product Managers work with cross-functional teams of engineers, solutions architects, data scientists and customer-facing partners to take conversational AI agents from prototype to production at scale. This is a deeply technical, hands-on role for someone who has already shipped and operated live agentic systems in front of real users, and who can own end-to-end system design, evaluation and hillclimbing while leading AI transformation with our largest partners.
Responsibilities
- Be responsible for leading and driving a complex product area; defining success, prioritizing problems and identifying the best strategies, considering wider organizational and company context.
- Adapt and adjust your strategies to reflect learnings and changes in context.
- Identify and drive consensus for how to prioritize and realize the most significant opportunities in your product area.
- Identify when to stop as well as when to start investment.
- Critically evaluate when AI is (and isn't) the optimal solution, with sophisticated articulation of tradeoffs, risks, and second-order effects.
- Translate AI capabilities into compelling product visions that create differentiated value.
- Develop and champion AI-native strategies including comprehensive evals and data strategies that enable continuous improvement.
- Work with a cross-functional team to define a product vision, develop a roadmap and drive progress against goals and milestones and resolve challenges and blockers, whilst improving team health and up-leveling the effectiveness of the team.
- Actively identify opportunities and resolve dependencies by creating shared strategies across teams in adjacent product areas.
- Reimagine workflows, responsibly using AI tools to dramatically increase team velocity and capability.
- Foster a culture of rapid experimentation and learning across the organization.
- Scale AI best practices (including responsible AI use), workflows, and artifacts across product teams so the org's capability compounds over time.
- Support the growth of other PMs and cross-functional team members by providing mentorship and coaching on AI-native practices.
- Influence strategy and progress across partner functions, enhancing collaboration and resolving divergent goals.
- Orchestrate complex execution across multiple workstreams by combining AI automation with strategic human oversight—using AI to reduce toil while maintaining high quality and accountability.
- Communicate product strategy and progress with radical clarity to all stakeholders.
- Use AI-enabled tools to build products—independently creating tangible artifacts to prototype, validate, or ship.
- Interpret research and state-of-the-art learnings to design product strategy and apply rigorous logical reasoning.
- Demonstrate deep understanding of system/architecture trade-offs and how they impact user experience and business outcomes; lead credible technical discussions with engineering partners.
- Gather and analyze user research and market analysis to inform product decisions and influence the wider product organization.
- Design sophisticated experiments and interpret results (leveraging AI to accelerate analysis) and drive concrete product decisions.
- Define and run evaluations to interpret model outputs and adjust execution based on learnings—establishing evaluation as a first-class product practice across teams.
Minimum Qualifications
- 8+ years of relevant industry experience with at least 3 years in Product Management
- Demonstrated ability to derive product direction from production system data — deciding what to build next from evals, telemetry and user failure modes rather than from stated requirements
- Experience leading cross-functional team(s) across a full product line: Crafting product mission and strategy, defining product requirements, coordinating resources from other groups (marketing, legal, etc.), and driving the team to achieve key milestones and goals
- Demonstrated experience in communication, bringing extreme clarity to complex and technical messages across all audience levels
- Experience leading and motivating teams and influencing across an organization
- Demonstrated proficiency using AI-enabled tools to build product artifacts
- Experience integrating a diverse set of requirements from a broad set of users as well as context into a single coherent product strategy
- Experience identifying and hiring the right talent to build an AI-capable cross-functional team
- Extensive understanding in analyzing large scale, complex data sets and making effective decisions based on data
- Experience with comprehensive AI evals, monitoring and data strategies that enable continuous improvement of deployed AI systems
- Proven experience to drive a step change in the performance of a product and the effectiveness of the team that delivers that product
- Bachelor's degree (or relevant degree equivalent): STEM subject ideal but not essential (Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences)
Preferred Qualifications
- Advanced degree in Computer Science, Machine Learning or a related technical field
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Demonstrated experience deploying and operating conversational AI in a regulated, high-volume or mission-critical customer facing environment - including end-to-end system design and API architecture, tools and protocols drive end-to-end automation
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