OverviewThe AI-Native Product Lead is a team-embedded product role responsible for translating business needs into clear, testable, and technically actionable requirements and owning the product backlog for a single AI-Native team. This role serves as the product owner for the team, working closely with the AI-Native Tech Lead and engineers to ensure the team is focused on building valuable, usable, and high-quality software.
This role focuses on solution definition through requirements gathering, feature and user-story creation, backlog prioritization, and story acceptance, while operating within a small, focused team and enabling delivery through AI-assisted engineering workflows. A key responsibility of the AI-Native Product Lead is to provide product intent and grounding context that guide both human and AI-assisted development. This includes clearly articulating problem statements, constraints, desired outcomes, and acceptance boundaries so that implementation decisions
remain aligned as delivery accelerates.
The AI-Native Product Lead also performs high-fidelity epic validation, ensuring epics are sufficiently precise, well-scoped, and grounded before decomposition into features and stories. This validation reduces ambiguity, prevents downstream rework, and enables effective use of AI-assisted development.
The AI-Native Product Lead ensures the team builds the right capabilities, with the right scope, at the right time, while maximizing delivery speed and quality. The AI-Native Product Lead does not need to be an AI or ML specialist but must understand how AI-enabled development changes delivery speed, iteration cycles, and product discovery.
Responsibilities
Principal Responsibilities and Essential Duties:
Product Ownership
- Own the single-team product backlog.
- Ensure continuous backlog readiness to support fast, iterative delivery.
- Make day-to-day scope and sequencing decisions to minimize delivery friction and rework.
Requirements & Solution Definition
- Conduct interviews and requirements workshops with business and technical stakeholders to elicit and clarify business needs.
- Translate business needs into well-structured, testable requirements.
- Maintain clear, precise documentation that enables efficient and accurate implementation.
Product Intent & Grounding Context
- Provide clear product intent by articulating the problem being solved, desired outcomes, and constraints.
- Supply grounding context for both engineers and AI-assisted development workflows, including domain assumptions, user behaviors, system invariants, and acceptance boundaries.
- Ensure intent and context remain current as requirements evolve, preventing misalignment.
- Act as the primary source of truth for what success looks like at the epic, feature, and story level.
High-Fidelity Validation
- Perform high-fidelity validation of epics before decomposition into features.
- Ensure epics are sufficiently precise, well-scoped, and grounded to support AI-assisted implementation.
- Identify & resolve ambiguity, hidden assumptions, and incomplete intent early to reduce downstream rework.
- Validate that epics are actionable, testable, and aligned with architectural constraints prior to execution.
- Serve as a quality gate ensuring epics are ready for accelerated delivery within an AI-Native dev model.
Continuous Delivery Validation & Outcome Alignment
- Continuously validate work against product intent, grounding context, and expected outcomes as implementation progresses.
- Provide in-flight clarification and refinement of requirements to maintain alignment as engineers and AI-assisted workflows iterate rapidly.
- Perform incremental acceptance of capabilities as they emerge, focusing on correctness, completeness, and behavioral alignment rather than ceremony milestones.
- Ensure delivered functionality is usable, extensible, and aligned with domain constraints, system boundaries, and quality expectations.
- Detect gaps between intended and actual outcomes early and drive corrective action before scale or automation amplifies defects.
Stakeholder Communication
- Communicate progress, scope tradeoffs, risks, and delivery outcomes to stakeholders.
- Act as the primary product point of contact for the AI-Native team, ensuring alignment between business intent and engineering execution.
Complete all responsibilities as outlined on annual Performance Plan.
Complete all special projects and other duties as assigned.
Must be able to perform duties with or without reasonable accommodation.
Qualifications
- Bachelor’s degree in a related field or equivalent practical experience.
- 6+ years’ experience in product ownership, product management, or business analysis roles within Agile delivery environments.
- Strong experience translating business problems into clear, testable product and technical requirements.
- Excellent written and verbal communication skills.
- Proven analytical and problem‑solving skills, with experience in systems modeling, workflow analysis, or solution design.
- Ability to learn complex domains quickly; healthcare experience preferred.
- Experience with systems modeling, user interface design, and prototyping, decision trees, data flow.
- A wide degree of creativity and latitude is expected.
Mental Requirements:
- Critical Thinking: Ability to think critically and evaluate information objectively, considering different perspectives and potential implications before drawing conclusions or making recommendations.
- Attention to Detail: must have a keen eye for detail to ensure accuracy in data analysis, interpretation, and reporting.
- Quantitative Aptitude: Strong numerical skills are essential for conducting quantitative analysis, working with statistical methods and models, and manipulating data using mathematical operations.
- Data Interpretation: skilled in interpreting data visualizations, charts, graphs, and other forms of data presentation to extract meaningful insights and communicate findings effectively.
- Communication Skills: Effective communication skills are crucial for conveying complex technical concepts and insights to non-technical stakeholders clearly and understandably through written reports, presentations, and verbal discussions.
- Curiosity and Learning Agility: A strong desire to learn and explore new methodologies, techniques, and tools in the field of data analysis and insights generation is essential for staying current with industry trends and best practices.
- Resilience: The ability to handle pressure, adapt to changing priorities, and overcome setbacks is important in a fast-paced and sometimes ambiguous analytical environment.
- Ethical and Integrity: Upholding ethical standards and maintaining integrity in handling sensitive data and information is paramount for building trust and credibility in the insights provided.
Physical Requirements and Working Conditions:
- Remaining in a stationary position, often standing or sitting for prolonged periods.
- Repeating motions that may include the wrists, hands, and/or fingers.
- Must be able to provide a dedicated, secure work area.
- be able to provide high-speed internet access/connectivity and office setup and maintenance.
- No adverse environmental conditions expected.
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Base compensation ranges from $90,000 to $124,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.
This role is based remotely and all interviews will be conducted virtually.
Date of posting: 03/16/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 06/15/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
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