Product Managers who value moving quickly and demonstrate AI-native product development practices.

Responsibilities

Responsible for leading a product area; defining success metrics, prioritizing product problems and identifying the best strategies for the product, aligned with the organizational goals.
• Adapt and adjust your strategy to reflect learnings and changes in the product.
• Critically evaluate when AI is (and isn't) the right solution for user problems, with clear articulation of tradeoffs and risks.
• Translate AI capabilities into compelling product visions grounded in real user value.
• Develop AI-native strategies including evals strategy and data strategy that enable iteration and measurable quality improvements.
• Leverage AI for identifying opportunities through deep market research, user feedback synthesis, and competitive analysis.
• Work with a cross-functional team to define a product, develop a roadmap and drive progress against goals and milestones and resolve challenges and blockers, while maintaining team health.
• Reimagine workflows, responsibly using AI tools to increase personal and team velocity (e.g., faster synthesis, clearer decision docs, tighter iteration loops).
• Foster a culture of rapid experimentation and learning, especially around AI-powered product development.
• Scale AI best practices (including responsible AI use) and proficiency across product teams to multiply impact.
• Provide mentorship and coaching to other Product Managers and cross-functional team members on AI-native practices.
• Coordinate proactively across partner functions for product success.
• Structure shared roadmaps for best outcomes.
• Orchestrate complex execution across multiple workstreams by combining AI automation with appropriate human oversight.
• Communicate product strategy and progress with clarity to all stakeholders.
• Use AI-enabled tools to build products-prototyping, validating, or shipping tangible artifacts independently.
• Interpret research and state-of-the-art learnings to design product strategy and apply logical reasoning.
• Understand system/architecture trade-offs and how they impact user experience and business priorities and engage credibly with engineering partners on constraints and decisions.
• Design experiments and interpret results (leveraging AI to accelerate analysis) and turn insights into concrete decisions.
• Define and run evaluations (evals) to interpret model outputs and adjust execution based on learnings-treating evaluation as a first-class product practice.

Minimum Qualifications
• 5+ years of relevant industry experience with at least 2 years in Product Management
• Bachelor's degree (or relevant degree equivalent): STEM subject ideal but not essential (Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences)
• Experience working with a cross-functional product team on a significant product area: Crafting product vision and strategy, defining product requirements, coordinating resources from other groups (marketing, legal, etc.), and driving the team to achieve key milestones and goals
• Experience managing a product through multiple product life cycle phases
• Proven experience to drive a material change in the performance of a product and the effectiveness of the team that delivers that product
• Demonstrated experience to analyze large scale, complex data sets and making effective decisions based on data
• Experience using AI-enabled tools to build product, prototypes, or other tangible product artifacts
• Demonstrated ability to develop AI-native strategies including evals and data strategies
• Experience integrating a diverse set of requirements from a broad set of users as well as context into a single coherent product strategy
• Experience leading and motivating a product team and collaborating with partner teams
• Demonstrated experience in communication, bringing extreme clarity to complex and technical messages at the appropriate level for the audience

Preferred Qualifications
• 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