Responsibilities
- Lead product vision, planning, and execution quality for key talent-facing platforms including the AI Coach, Career Passport, training and job matching interfaces, and data-driven AI features.
- Leverage AI agents and large language models such as Claude, Cursor, and v0 to independently build prototypes, develop test strategies, and analyze customer feedback.
- Independently conduct discovery, generate design alternatives, draft specifications, create development tickets, and validate solutions with users in rapid cycles.
- Determine when to deploy automated AI agents versus when to engage human expertise, making strategic judgments on where AI accelerates progress and where engineering is essential.
- Establish best practices for AI-native product development and create repeatable workflows adopted across the team.
- Conduct ongoing, low-overhead user research through interviews, session reviews, and data analysis to identify core problems and generate testable design hypotheses.
- Quickly build functional prototypes using AI tools, no-code platforms, and joint engineering sessions to test concepts with users before formal PRDs.
- Facilitate structured discovery workshops to understand job seekers’ needs when planning their next career moves.
- Stay informed on workforce development regulations, including WIOA, Workforce Pell, and Eligible Training Provider List (ETPL) policies.
- Convert technical architecture decisions and engineering context into well-defined, actionable development tasks.
- Write detailed product requirement documents and technical specifications with clear success criteria, edge case handling, data needs, and testable completion standards.
- Manage a multi-quarter product roadmap for the Talent Journey area, aligning feature development with the company’s broader strategic goals.
- Participate in high-level product strategy discussions with senior leadership, including the CPO, data and engineering leads, and workflow leads.
- Break down company-level strategy into a logical, sequenced implementation plan, clarifying what to build, when, and what to defer.
- Conduct market and competitor research on job seeker-facing workforce tech, focusing on AI-first products and government digital transformation efforts.
- Define how user profiles are built for the AI Coach, including data collection methods and use in autonomous agent systems.
- Create a measurable framework to assess AI Coach performance, defining quality benchmarks, metrics, and feedback mechanisms with the data team.
- Discover and prioritize opportunities to enrich Career Passport data—such as skills assessments, training records, and employer signals—to improve data completeness and reliability.
- Ensure job seeker privacy and trust are central to all data design choices, identifying risks and collaborating with legal and engineering on compliant solutions.
- Advocate for job seekers in planning and prioritization discussions across teams.
- Collaborate closely with engineering leads from architecture design through sprint planning to align user needs with technical delivery.
- Support data teams in defining job seeker analytics: determine key metrics, measurement approaches, and data warehouse requirements.
- Oversee end-to-end launch readiness, including coordination with customer success and go-to-market teams, rollout conditions, and post-launch feedback collection.
- Work with Customer Success and GTM teams to equip state agencies and employers with clear messaging about job seeker products.
- Coordinate with the Senior TPM for Customer Workflows to ensure seamless integration between job seeker and employer-facing systems.
Work Arrangement
Hybrid — CA/US Remote, Toronto, Canada, New York, US
Team
Team of 30-50 people including Product, Engineering, Data, Growth, Customer Success, People & Culture, and Finance & Operations
Other
- Travel: up to once per quarter for offsites and team gatherings.
- Hiring process generally takes around 6 weeks.
- Reasonable accommodations available for individuals with disabilities upon request.
- AI is used in hiring for screening support and interview notetaking, but final decisions are made by humans.
