Lead Product Engineer (Irvine) - On-Site

Eggs Unlimited•Irvine, CA

1d•$180,000 - $210,000•Onsite

About The Position

We leverage AI to bring food to every table. You are a hands-on product engineer embedded with operations. You find the workflow problems worth solving, build and run the software that solves them, and own whether the business actually adopts it. AI-assisted development is how the work gets done. Human judgment, controls, and production quality are not negotiable. We are building the intelligent operating platform behind a global food supply chain, combining leading models, our own operational data and business rules, and the judgment of the people who trade for a living. The product layer is largely greenfield. You will be building it, not maintaining someone else's version of it, though it has to work with the operational systems the business already runs on. We move quickly and we build practical solutions that scale, not demos.

Requirements

Demonstrated experience with product discovery, requirements synthesis, and prioritization in real operating environments.
You ship production code. You are accountable for what it does in production, however it was produced.
Serious agentic development practice. Show us real parallel-agent work: how you decompose tasks, manage context, review and reconcile output, design tests and evaluations, an example of a failure you caught, and a case where you decided not to use an agent. Anonymize anything confidential.
Ownership. You have carried something end to end and been accountable for whether it worked, not for whether it shipped.
Enough backend, data, and deployment competence to design APIs and data models, integrate systems, deploy and instrument services, and debug production issues independently, while working with platform, security, and domain experts where it matters.
Judgment about correctness in nondeterministic systems: evaluations, observability, failure-mode thinking, guardrails, human escalation, and rollback.
You can make technical decisions and tradeoffs understandable to people who are not engineers, document them clearly, and take operator feedback on board.
Experience building within messy operational reality, email, spreadsheets, chat threads, and phone calls, rather than replacing it with something tidier that operators will not adopt.
We do not screen on years of experience, and we do not screen on which technologies you have used. Seniority here is calibrated by scope, judgment, autonomy, and outcomes. Show us what you have built.

Nice To Haves

Food distribution, logistics, retail and CPG, trading, ERP or EDI, financial operations, or other trading-partner ecosystems.
Ambiguous, high-ownership environments where defining and building were tightly coupled, for example as a founder, early employee, product engineer, or forward-deployed engineer.

Responsibilities

Observe the workflow first, then interview operators to validate what you saw. Identify the work that can be safely automated, and the work that must stay under human judgment.
Decompose a problem into work that can run in parallel, direct agents at it, control context, reconcile conflicting output, test what comes back, and remain responsible for the final system.
Own the path from a validated need to monitored production. The platform team supplies tooling, guardrails, CI/CD, evaluation infrastructure, and architecture and peer review.
Partner with operators and their managers on rollout, training, feedback, and iteration, and stay accountable for whether adoption is real rather than announced.
Every release should remove more operational burden than it adds, use the channels operators already work in, need almost no instruction to adopt, and fail safely and visibly.
Own the backlog for your domain and the order of work, co-owned with the business leaders whose desks are affected, with the tradeoffs written down.
Define done in the operators' own terms, hours saved, loads moved, claims recovered, follow-ups caught, against a baseline you established first. Report honestly on how often the system is right, how often it is wrong and in which direction, and how often it escalates to a person.
Ship maintainable, tested, observable, secure systems, with explicit evaluations, audit trails, rollback paths, and safe failure modes. Agent-generated work is held to the same production standard as anything you type.