Technical Product Owner, AI-Directed Development
cbtnuggets · Eugene, Oregon, United States · United States · remote
Why CBT Nuggets is a great place to work:
Work from anywhere. While we have an office in Eugene, Oregon, the majority of our team works remotely throughout the United States.
We take work-life balance seriously. You’ll work hard at CBT Nuggets, but you’ll also have plenty of time to relax and recharge. We recognize the importance of spending time with your family and friends — and having time for your hobbies and passions.
Enjoy creative freedom. Got ideas that could benefit our learners and organization? We embrace innovation. We are always open to new ideas — and welcome them from everyone on our team.
Get involved in great causes. NuggetLove, our charitable arm, is committed to making a difference. We support a wide range of issues ranging from education to social justice to supporting military personnel who are transitioning to civilian life.
SCOPE & GENERAL PURPOSE OF JOB:
You will own the day-to-day health and growth of two production products: the CBT Nuggets website and the Assessments platform. You will not write code. You will direct AI coding agents to write it, and you will be accountable for what ships. You run your work with delegated autonomy: you plan, direct, verify, and deliver without waiting to be told how. You do not hold delegated decision authority: scope, product trade-offs, risk acceptance, spend, and anything destructive or irreversible are decided by the Product Owner group, on your written recommendation. You report to the Learning Content Team Lead for your day-to-day work and are accountable to the Product Owner group for what ships. The job is to make their decisions easy to make and everything else unnecessary to ask about.
DELEGATED AUTONOMY, RETAINED AUTHORITY:
- How to break a defined piece of work into tasks and in what order.
- Which agents to run, with what instructions, in what sequence.
- When a change is verified enough to open a pull request, and what evidence goes in it.
- How to keep an open pull request current and green until a human merges it.
- Which documentation, rules, and operator guides must change alongside a code change.
- How to investigate a production problem and what evidence to gather.
- When to stop and escalate.
- Adding, removing, or changing a feature a learner, customer, or admin can see.
- Any change to pricing, plan structure, public claims, or published copy that states a fact.
- Accepting a risk: a security advisory left open, a test weakened, a check made advisory, a known limitation shipped.
- Changing which AI model, vendor, or threshold a production system uses.
- Spending money: new services, tiers, seats, paid tooling.
- Changing a contract with another team or system (the CRM, Adept, the shared header contract, the data warehouse).
- Deleting or migrating data, dropping columns, rotating credentials, changing access.
- Merging a pull request. A human merges.
- Proceeding on a question the Product Owner group has not actually answered. A skipped, timed-out, or lost answer is not an answer.
- Letting an agent's confidence stand in for verification.
- Storing learner personal data where the rules say it must not be stored.
- All three roles share the profile above and are interchangeable in an emergency. Each carries a primary surface so the team has depth where it matters.
- Assessments and data. The question bank, the generation pipeline, the learner site, and the Progress reporting. Second skill: data literacy and measurement. You will spend time in the warehouse and in model evaluation evidence.
- Website, conversion, and copy. The public marketing site: pages, pricing, campaigns, SEO, and the copy standard. Second skill: editorial judgment and audience focus. You will own the voice and the truth of every public claim.
- Platform, security, and integrations. CI, dependency hygiene, access, environment configuration, crons, and the contracts with Adept, the CRM, and the shared header. Second skill: security and risk judgment. You will own the advisories and the risk register.
- State which surface you prefer when you apply. We will balance the three.
- Not a hands-on development role. If you want to write the code yourself, this will frustrate you.
- Not a people management role. You lead agents and influence peers; you do not manage staff.
- Not a role with final say. You will recommend often and decide within your lane. The lane is wide. Its edge is firm.
- Both products run on Next.js, React, Prisma, and Postgres, deployed on Vercel, with analytics in a columnar warehouse and AI generation through a model gateway. Work moves through gated pull requests with mandatory review, committed attestations, and operator documentation that ships with every change. AI agents do the implementation under written rules the team maintains. The rules are the product as much as the code is.
- First 30 days. You have shipped changes through the full gated workflow on both products. You have read the operating rules and can explain why each exists. You have found and corrected at least one stale claim in the documentation.
- First 90 days. You own a surface. Your pull requests arrive green and stay green. Your escalations are answerable in a sentence. You have written at least one durable rule from a lesson you learned, and retired one that was stale.
- First year. The Product Owner group can leave your surface for a month and return to find it healthier, better documented, and with a short, well-argued list of decisions waiting. Nothing shipped that they would not have approved. Nothing waited that they would have approved in a sentence.
- Specification exercise. Given a short product request, write the specification you would hand to an agent. We are reading for precision, missing cases, and whether you identified what needs a decision from the Product Owner group.
- Review exercise. Given a pull request with an agent-written summary that over-claims, find it, say how you found it, and say what rule would prevent it next time.
- Escalation exercise. Given a situation with real trade-offs, write the one-page recommendation. We are reading for whether the decision-maker can answer in a sentence.
- Business conversation. Tell us what you learned about CBT Nuggets from public sources and what you would want to measure first.
PRIMARY RESPONSIBILITIES:
- Own a backlog for your surface. Turn product intent into precise written specifications an AI agent can execute without guessing.
- Direct AI coding agents through the full change lifecycle: specification, implementation, review, tests, documentation, pull request, CI, and production verification.
- Read every diff critically. Find the over-claim in an agent's summary before a reviewer does.
- Operate the repositories as a professional: branch protection, required checks, rebases, attestations, dependency advisories, environment variables, crons, feature flags, deployments.
- Keep the operator documentation true. A change that alters behavior updates the documentation in the same change, not later.
- Turn every lesson into a durable, dated rule that the next agent and the next teammate must follow. Retire rules that have gone stale.
- Investigate production incidents from logs, metrics, and the database, and write up what happened and what prevents it.
- Measure before you claim. Date every reading. Record when an earlier reading turned out to be wrong.
- Reduce friction for other humans. When a decision or a labeling task needs a person, build them a page with buttons and send a link, not a document with instructions.
- Work in the open with your two teammates: shared rules, shared conventions, no private process.
SKILLS/COMPETENCIES/EDUCATION:
- Skills/experience required:
- Five or more years in IT or software, in roles that required understanding how production systems are built, deployed, secured, and operated. Systems administration, network engineering, DevOps, QA engineering, solutions engineering, technical support leadershi