AI Engineering Systems Lead

We believe most of the code in our platform is going to be authored by AI, and that this changes the job of architecture, not just the speed of typing. LLMs are brilliant at producing code that looks right and runs on the first try. They are unreliable at remembering the invariants that keep a large system correct. A platform that only works when the author remembers the rules will quietly rot under AI authorship.

So we made a different bet. We build the machinery that makes the rules impossible to break: deterministic checks, compile-time types, runtime guardrails, and autonomous pipelines that ship code through all of it. We’re well into this work. We need someone to own it and push it to the frontier.

Why Rootstock, why now: Rootstock brings proven depth in ERP and manufacturing - real products, real customers, decades of hard-won domain knowledge. We’re putting that depth behind a clear blueprint for becoming AI Native, with active development underway and the funding to see it through. You’d build alongside a deep bench of senior engineers who have shipped real ERP at scale. Iron sharpens iron.

The role in one line: You own the internal systems that let Rootstock engineers - and our agents - ship production Salesforce code fast and ship it correct. What you’ll actually build

This isn’t a greenfield daydream. There’s real, running scaffolding for you to take ownership of and extend:

• Autonomous coding pipelines. A bugfix pipeline already turns a Jira ticket into a reviewed Apex/LWC pull request, with an observability layer that scores every run. You’ll deepen it, widen it to new pipeline types, and raise the bar on how autonomously and reliably it ships.
• A root-cause engine, and the evals that keep it honest. One of our most important tools investigates a bug across multiple repos and millions of lines of code to find the actual root cause, grounded in a continuously built specification corpus. Evals run constantly - we pit the current generation against candidate generations and against fixes real engineers actually shipped. You’ll own it and keep pushing it forward.
• A ‘Constitution’ of enforced architecture. We maintain foundational architectural decision records that bind every repo, on a single thesis: every principle must have a deterministic enforcement seam - a type, a startup check, a CI test, or a hook - never just a doc. You’ll extend this and the runtime that enforces it across the Claude Code session lifecycle.
• TDD tooling that actually changes behavior. A local in-memory Apex test runner lets engineers run the red-green-refactor loop without deploying to an org. You’ll build the tooling that makes test-first the path of least resistance, for humans and agents alike.
• The guardrails. A suite of quality and safety hooks that format, scan, and block bad edits before they land, plus the PR gate that runs the full scanner suite. You’ll decide what the next generation looks like., Lead end-to-end execution of packaging category sourcing across assigned markets: manage supplier relationships, run RFP/RFI and contract negotiations, ensure supply continuity and risk mitigation, drive supplier performance and cost optimization, and collaborate with cross-functional teams to deliver category outcomes for the QSR system.

• A strong systems and types thinker. You reach for the type system, the lint rule, or the CI test to make a class of bugs unrepresentable, rather than writing a paragraph in a style guide.
• Real fluency with AI-assisted and agentic development. You’ve built with agents, you have opinions about where they break, and you’ve designed around their failure modes.
• Solid programming fundamentals. Competence in Java, JavaScript, or something comparable translates well - strong engineers pick up the rest.
• Comfort building developer tooling, CI/CD, and orchestration: hooks, pipelines, observability. You like making other engineers faster.
• Salesforce and Apex experience is a plus, not a gate. We care more about how you think about platforms than how many years you’ve shipped on any one of them.

Own and advance internal systems that let engineers and agents ship correct Salesforce production code: autonomous coding pipelines, root-cause analysis and evals, enforced architecture via deterministic checks, local Apex test tooling, and quality/safety guardrails. Extend observability, CI/CD, and orchestration to make test-first and agentic development reliable at scale. The summary above was generated by AI AI Engineering Systems LeadMost engineering orgs are bolting AI onto how they already work. We’re rebuilding the work itself., * You build things for fun. Have you ever shipped a side project just because you wanted to see if it would work? We want to hear about it.

• You enjoy experiment, trial, failure, and rapid iteration - and you instrument your way out rather than freezing when the first attempt fails.
• You’ve built a proof of concept just to test a theory, and killed one just as happily when the data said no.
• You’re a self-directed learner who’s eager to leave a real mark on how an organization builds software. There is enormous surface area here and very little bureaucracy in your way.

How we work

We do genuinely new things, and new things fail often. We expect to chase ten ideas and have seven hit dead ends. Nobody gets punished for a smart bet that didn’t pay off - the job is to run the experiment, learn from it, share what you found, and keep moving. We write up our dead ends openly, because a well-understood failure shapes the next decision as much as a win does, often more.

We care as much about raising the whole team as we do about shipping the next tool. People here treat helping a teammate level up on AI as the fun part, not a tax on their time. No egos. We push each other to get sharper. What we’ll go deep on in interviews

Our interviews are not trivia. Expect to go deep on models and their tradeoffs, the AI-assisted systems you’ve built, the hardest problems you’ve hit building with AI, eval and measurement, and where you think agentic coding is actually going. Bring your strong opinions and your scars. The basics

• Location: Remote, US-based
• Visa Sponsorship: This position requires authorization to work in the US; we are unable to provide visa sponsorship, including H-1B.
• Compensation: Base salary, annual bonus, and a long-term incentive plan (LTIP). We set the level by experience - show us what you’ve built. Your work has a direct line to the LTIP upside.
• Tooling: Claude license, full access to Salesforce’s AI tooling, approved API spend, and budget for local model experimentation. We don’t want cost to be the reason you didn’t try something.
• How to apply: Send us the work - repos, demos, write-ups, the proof of concept you couldn’t stop tinkering with. A link to something real is worth more than a polished résumé. Please include your desired salary range.

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