Technical Product Manager, AI and Data

Accountabilities

• Own and sequence the AI and data product roadmap, partnering directly with engineering leadership and senior company stakeholders to determine priorities, timing, and tradeoffs.
• Define and drive the development of AI-powered product experiences across multiple customer segments, with a strong focus on adoption and measurable outcomes rather than simply launching features.
• Establish appropriate evaluation standards for AI products, ensuring that outputs are reliable, trustworthy, and suitable for use in a health-focused environment.
• Prioritize incoming requests and competing opportunities so engineering teams remain focused on the highest-value product and technical initiatives.
• Partner closely with data engineering to strengthen the analytics and data foundation used for product decisions and broader business operations.
• Define success metrics and evaluation criteria before features are developed, analyze performance after launch, and make decisive adjustments or discontinue initiatives that do not deliver expected value.
• Translate rapidly evolving AI capabilities and technical constraints into clear product strategies and an actionable sequence of initiatives.
• Build strong working relationships with engineering and AI teams, contributing meaningfully to technical decisions and earning credibility through a strong understanding of software, data, and AI systems.
• Connect near-term product decisions to longer-term consequences, clearly identifying tradeoffs and maintaining alignment with broader product and business objectives.
• Promote a culture of ownership, experimentation, continuous learning, direct communication, and customer-focused problem solving.

Requirements

• 3–5 years of professional product management experience, currently operating at a Product Manager or Senior Product Manager level.
• 4–8 years of hands-on engineering experience earlier in your career, ideally as a software engineer or in a comparable technical position.
• Demonstrated experience taking AI-powered products from development into production, rather than working exclusively on prototypes or internal experiments.
• Strong ability to independently determine what should be built in a rapidly evolving technical environment and confidently defend product decisions using sound reasoning.
• Deep understanding of AI capabilities and limitations, including the ability to explain what a particular AI technique can and cannot accomplish for a specific product problem.
• Strong technical credibility and the ability to collaborate effectively with engineers and AI specialists on complex technical decisions.
• Strong analytical and quantitative skills, with the ability to structure complex or messy data and develop conclusions that can withstand detailed scrutiny.
• Ability to influence skeptical stakeholders through clear reasoning, evidence, and compelling communication rather than relying on authority.
• Strong ownership mentality, proactive problem-solving skills, and comfort operating independently in ambiguous environments.
• Excellent written and verbal communication skills, with the ability to communicate effectively across technical and non-technical audiences.
• Experience working in a fast-paced startup or similarly dynamic environment is preferred.
• Experience in healthcare, life sciences, regulated data environments, DTC health or wellness is preferred.
• Experience supporting or scoping a data warehouse, analytics infrastructure, or similar data initiative is a plus.
• Experience working effectively in remote environments and familiarity with collaborative tools such as Slack is preferred.
• A self-directed, resourceful approach and willingness to learn quickly are essential.

Benefits

• Fully remote work environment across the United States and Canada.
• Remote-first culture with working hours aligned within a two-hour window between 9 AM and 6 PM CST.
• Opportunity to shape AI-powered products and data capabilities within an ambitious, mission-driven organization.
• High level of ownership and direct influence over product strategy, priorities, and execution.
• Collaborative environment with close access to engineering leadership and senior company stakeholders.
• Culture focused on experimentation, transparency, accountability, continuous learning, and customer impact.
• Opportunity to work on challenging AI and data problems in a health-focused environment.
• Strong emphasis on autonomy, resourcefulness, and professional growth.