Lead Product Engineer - On-Site (Irvine)

Eggs Unlimited; Irvine (CA); On-site; USD 180,000 - 210,000; Full time

Benefits offered by this job

Daily lunch

Medical coverage

401(k) match

Job summary

Eggs Unlimited is building an intelligent operating platform behind a global food supply chain. You will be a hands-on product engineer embedded with operations, owning the discovery to delivery loop and ensuring adoption by traders, coordinators, and logistics desks.

You will work across Go, Python, and TypeScript in a fast-paced environment, shipping production code that scales with the business. The role emphasizes ownership, judgment, and measurable impact on operational burden.

Qualifications

• Demonstrated experience building production systems in real environments.
• Ability to turn discovery into deliverable software with measurable impact.
• Comfort working across business domains including trading, logistics, and ERP data.

Responsibilities

• Observe workflows, interview operators, and identify automations that reduce manual work.
• Decompose problems, orchestrate parallel agents, and own end-to-end delivery in production.
• Collaborate with traders, purchasing coordinators, and logistics desks to ensure adoption and value.
• Define metrics and monitor operator-focused outcomes such as hours saved and loads moved.
• Build scalable, secure, and observable systems with robust guardrails and rollback paths.
• Own the backlog and sequencing with business leaders to align outcomes with desks' needs.

Skills

Product discovery

Ownership

Backend development

APIs design

Tools

Go

Python

TypeScript

APIs

Job description

Eggs Unlimited is one of the worlds largest suppliers of eggs, servicing the biggest retail and food manufacturing companies around the globe. Every day, we find homes for millions of eggs by tapping into our vast supply chain and customer networks. Bringing sellers and buyers together in fair market negotiations, we open up a world of possibilities for expanding their knowledge, reach, and access. With dedicated service teams and a mission to uphold transparency and trustworthiness, we create quick and creative solutions to help manage the ever-evolving demands of the global egg industry.

The Role

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.

The Problem We Are Solving

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. Extracting an order from an email is no longer the hard part. The loop is. Forecast where the market is going, project demand forward by customer and by product, and know what we are long and short on any given day. Then decide what to buy and what to sell, build the load, and book the freight against a computed view of what that lane is actually worth. Trading, supply, freight, and the ledger stop being separate systems stitched together by a spreadsheet and become one connected flow, with a named person accountable at every point where money moves. 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.

The Orchestrator

The person in this seat does not write a specification and wait. They take an idea, direct a fleet of agents at it, and produce a working implementation themselves, at a volume of output that would not have been possible from one person two years ago. If your monthly token consumption would look alarming to a traditional engineering manager, you are probably working the way we work. What we measure is not the volume: it is whether you decompose work well, keep context under control, catch the plausible and wrong answer, and stand behind what ships. You do not need prior experience in our exact stack. What matters is whether you can build things, whether you take ownership, and whether you can hold the big picture while you do it. Think like a customer, act like an owner. This seat pairs that with a product management background. You will sit with the traders, the purchasing coordinators, and the logistics desks, work out what the job is underneath the spreadsheet, and then own both halves: the discovery that finds the right manual burden to remove, and the delivery and adoption that make it stick. The goal is not to strip work out for its own sake, but to remove the burden while preserving the human judgment the business depends on.

What You Will Own

• Discovery at the Desk: 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.
• Agent Orchestration: 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. This is an operating capability, not a tool preference.
• Build and Ship It: 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.
• Implementation Across the Company: Your responsibility continues past the merge. Partner with operators and their managers on rollout, training, feedback, and iteration, and stay accountable for whether adoption is real rather than announced.
• Adoption Discipline: 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.
• Backlog and Sequencing: 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.
• Measurement in Operator Currency: 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.
• Engineering Standards: 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.

What Success Looks Like

• In your first 90 days: You know how at least two desks actually work, from sitting with them rather than from a document. One workflow problem chosen, with the baseline measured before anything is built. Something small in production that an operator uses by choice.

• In your first six months: One desk workflow measurably lighter: a documented baseline, a named operator owner, a measured reduction in manual work, and agreed behavior when it fails. A working evaluation and measurement layer for what you shipped: how often it is right, how often it is wrong, in which direction, and how often it hands back to a person. A prioritized backlog co-owned with business leaders, with sequence, tradeoffs, owners, and expected outcomes made explicit.

• In your first year: Production automation live across more than one operational function, each piece with a named owner, monitoring, rollback, an audit trail, and a stop path the desk itself controls. Adoption you can prove in operator currency: hours saved, loads moved, claims recovered, follow-ups caught, errors avoided.

The clearest sign that you are succeeding: operators bring you the next workflow, because the last one made their work better.

What You Bring

• 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.

Helpful Experience

• 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.

Team, Environment, and How Decisions Get Made

You report to the Director of Technology and join a small, senior engineering team. This is a lead role in scope and judgment, not in headcount: it does not manage people. The platform engineering lead sets the engineering and evaluation bar, owns shared tooling and guardrails, and is the second reviewer on your work. Infrastructure, identity, and access control sit with the platform team. Priorities are agreed with the Director of Technology and the business leaders who own the affected desks.

Our environment spans cloud services on Azure, relational and event-sourced data stores, services in Go and Python, a TypeScript front end, an enterprise ERP core, and a retrieval layer over the company's own operating history. You will not be expected to have used all of it.

Note: Responsibilities may evolve as the business grows and priorities change.

Why Eggs Unlimited

• Join at the "second floor" of a hyper-growth company rapidly becoming a skyscraper - help build what comes next.
• Outsized impact opportunity - building people, leadership, culture, & support continued expansion.
• Access meaningful advancement opportunities as the company continues to expand.
• Modern hardware and access to leading models and development tools, with clear security and data-handling guardrails rather than blanket tool bans.

Compensation and Benefits

• Base Salary: $180,000 - $210,000+ annually
• Comprehensive medical, dental, and vision coverage.
• Company-paid life and disability insurance.
• 401(k) plan with company match.
• Generous PTO accruals, increasing each year.
• Free daily lunch, snacks, and refreshments.