Remote AI-Native Product Lead: Backlog & Strategy

Overview

The 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. Thisrole serves as the product owner for the team, working closely with the AI-Native Tech Lead and engineers toensure 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, backlogprioritization, and story acceptance, while operating within a small, focused team and enabling delivery throughAI-assisted engineering workflows. A key responsibility of the AI-Native Product Lead is to provide product intentand grounding context that guide both human and AI-assisted development. This includes clearly articulatingproblem 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 specialistbut must understand how AI-enabled development changes delivery speed, iteration cycles, and product discovery.

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 domainassumptions, user behaviors, system in variants, 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.

This job description is intended to…