We're building the future of work: the Metamate platform, a full-stack product that allows people to direct, review, and help agents improve their work across the entire company. The ATA Product team builds the platform components, memory systems, improvement loops and shared product experiences that make AI useful for everyone. You'll be responsible for making Metamate excellent for everyone. You'll obsess over user needs and feedback, ensure interfaces like chat and web are as simple and intuitive as Meta's consumer products, and drive prioritization of new features.
Responsibilities
Own the Metamate product experience across all surfaces and modalities.
• Define and drive the UX strategy for power users who depend on Metamate daily for high-stakes work.
• Identify friction points, unmet needs, and interaction patterns through direct engagement with users and data.
• Partner with design, engineering, and research to ship improvements at pace.
• Set quality standards for agent interactions and hold the product accountable to them.
• Drive adoption and engagement metrics; define what "excellent" means and measure it.
Minimum Qualifications
• Strong analytical skills and comfort with ambiguity
• Ability to operate independently and make sound decisions with incomplete information
• Experience working with ML/AI-powered products
• Experience shipping consumer or enterprise products with high interaction frequency
• Track record of improving product quality through user insight and iteration
• 8+ years of product management experience
Preferred Qualifications
• Background in UX-intensive products (messaging, collaboration, creative tools)
• Experience with rapid prototyping and high-velocity iteration cycles
• Experience building for power users or productivity tools
• Deep personal fluency with AI tools and agents
• 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
