AI Enablement Product Manager

AI Enablement Product Manager

CONTRACTOR

Role Overview

● This contractor will help build and operationalize an AI-enabled Product Development Lifecycle (PDLC) suite of internal tools and
applications that help teams execute work faster and more consistently using AI agents, workflows, and relevant organizational
context.
● The primary users are product managers, designers, researchers, engineers, and program managers. Secondary users include
product marketing, customer success and support, sales, and their enablement teams.
● This is a hands-on product management and building role on an AI Enablement team.
What You'll Do
● Develop a deep understanding of business and user needs and translate them into clear requirements.
● Influence stakeholders and engineers using data, clear reasoning, and alignment on outcomes.
● Move quickly, communicate frequently, and surface risks early.
● Collaborate across Engineering, UX, Customer Success, and go-to-market teams.
● Identify longer-term investment opportunities and build support with partners.
● Own defined parts of the roadmap and collaborate with internal and external stakeholders to execute the product vision.
● Partner with others to define performance metrics and develop hypotheses for complex technical needs.
● Use insights from enterprise customers and technical subject-matter experts to train, enable, and scale product capabilities.
How This Role Is Different
● This is not a traditional externally facing product role. The product is an internal set of tools and workflows used by product teams
and adjacent functions.
● The contractor will initially work on specific tasks alongside the team lead and engineering, then ramp into ownership of defined
parts of the AI PDLC product with oversight as needed.
● The role combines product direction with active contribution to the build team. It is not simply a backlog-management or
feature-request role.
Ideal Candidate Profile
● Builds first and documents second: favors prototyping, testing, and shipping over writing about ideas.
● Uses AI tools daily and learns new tools through hands-on experimentation. Familiarity with Claude Code, Cursor, GitHub,
Codex, or comparable tools is valuable.
● Is comfortable working alongside engineers in repositories, pull requests, issues, branches, and developer environments. An
engineering background is not required, but technical fluency is important.
● Can operate as both product manager and builder, setting direction while contributing to internal tools and agent workflows.
● Proactively evaluates emerging AI tools and recommends practical adoption based on hands-on experience.
● Plans AI-first: designs work so agents can take the first pass, then collaborates with agents and teammates to refine and finish.
● Thrives in ambiguity and is comfortable helping shape a new function and ways of working.
● Understands real user workflows, identifies where AI can reduce friction or improve quality, prototypes in context, and iterates
based on adoption and feedback.
● Can teach and support colleagues with different levels of AI comfort through clear explanations and hands-on guidance.
● Treats adoption as a product outcome and measures whether workflows are used, where users drop off or work around them,
and whether they improve speed and quality.
Required Qualifications

● Bachelor’s degree or an equivalent combination of education and experience.
● 5+ years of related experience in software product management.
● Advanced capability in product requirements, data-driven decision-making, AI fluency, rapid prototyping, business acumen, and
product planning.
● Strong product judgment and the ability to work through ambiguity, evaluate complex problems, and make evidence-based
recommendations.
● Experience collaborating across functions and working closely with engineering teams.
Non-Negotiable Requirements
● AI-first workflow: already uses AI tools such as Claude Code, Cursor, Codex, or similar in day-to-day work and can demonstrate
current use.
● Technical proximity: comfortable with GitHub and common developer workflows; able to communicate fluently with engineering
partners.
● Builder mindset: can use AI tools to prototype ideas, write specifications, and create lightweight workflows or tools that engineers
or agents can productionize.
● AI tooling awareness: actively evaluates new tools and has informed opinions on what is worth trying.
● AI quality ownership: defines how AI-enabled workflows should be evaluated, tests outputs against real use cases, identifies
failure modes, and uses evidence to judge readiness to scale.
● AI skills library participation: willing to help translate requirements into AI skills, review contributed skills, approve submissions,
and maintain quality standards for a shared library.
● Time-zone overlap: must be based in a U.S. time zone that enables collaboration with the team (Eastern, Central, or Pacific).
Preferred Qualifications
● MBA degree.
● Track record of leading product vision and strategy.
● Experience delivering software in agile or continuous-deployment environments.
● Experience shipping products with strong customer experience and user feedback.
● Self-starter who requires minimal direction.
● Strong understanding of product development and web technologies.
● Strong leadership and ability to influence across teams.
● Excellent written and verbal communication, analytical, problem-solving, and prioritization skills.
● Willingness to travel up to 20%.
● Ability to ship lightweight internal tools with AI assistance, such as scripts, dashboards, or integrations.
● Experience with software factories, internal tooling, or developer productivity.
● Familiarity with agentic workflows in which agents take the first pass and people refine the result.
How the Role Operates
● Starts embedded on specific tasks with the team and ramps into ownership of defined roadmap areas and functionality.
● Partners closely with engineering as part of a build team, rather than operating as a feature-request intake function.
● Designs AI-first workflows in which agents take the first pass and the team applies judgment to refine and complete the work.
What This Role Is Not
● Not an externally facing product role serving external product customers.
● Not a traditional product manager role focused primarily on backlog administration and writing tickets for an engineering team.
● Not an engineering role with a small amount of product management added.

● Not a role for someone who is merely interested in learning about AI; hands-on daily use is expected.
● Not focused on utilitarian internal enterprise systems alone; the goal is to build a high-quality, consumer-grade experience for
internal users.