Builder Product Manager I

Our LBM customers are small and mid-size independent lumberyards, building material dealers and hardware stores who run their whole business on our ERP. It covers point of sale, inventory, special orders, delivery and contractor accounts. Dealers want software built for how a yard really works, so they can serve their contractors faster. The PM will need to be curious about the workflows end to end.

Most ERP companies are trying to "add AI" as a sidecar. We are using AI to rewrite the rules of how enterprise software is built, tested, and operated from the ground up.

As a Builder - Product Manager focused on our Lumber & Building Materials Products, you are the translator between ambition and execution. You aren't here to write PRDs that sit in Confluence; you are here to define the missions that the squad runs. You are likely the person who has replaced static roadmaps with living, AI-generated prioritization models and is now looking for a place where that isn't just "allowed," but is the core requirement. As you build new customer value driven enhancements/products you will work with the Industry PM and the Value Stream PM to guide you in overall strategy goals and key metrics for the applicable value stream are achieved.

CORE DNA — THE SHARED FOUNDATION

AI-native workflow

You have moved past writing requirements in Word docs. You use LLMs to synthesize user research, generate acceptance criteria, and stress-test your own assumptions before a single line of code is written.

Agentic implementation

You can specify and pressure-test the behavior of autonomous agents. You understand what LangGraph state machines do, and you can write the "Mission Brief" that constrains one correctly.

Legacy-to-modern bridge

You aren't afraid of 20-year-old ERP workflows. You see them as a map of latent user intent waiting to be extracted, re-expressed, and automated.

Deterministic mindset

You understand that "the PM said it was fine" isn't a guardrail. You define measurable acceptance criteria, quantitative evals, and the ground-truth definitions that let engineers prove correctness.

ELECTIVE SPECIALTY — THE MISSION ARCHITECT

While you share the Core DNA with the squad, your "Superpower" is translating complex ERP business logic into precise, executable agent missions:

Domain logic translation

You can take a 50-page accounting regulation or a decade of tribal knowledge from a SME and with the help of the Value Stream PM, turn it into structured system prompts, agentic constraints, and eval rubrics the squad can build against.

Agentic UX definition

Work with UX Research to define what "good" looks like when the interface is an AI agent, not a button. You write the behavioral specs (tone, escalation logic, failure modes) for generative UI experiences talking to customers to validate what you have built.

Eval ownership

You don't just define features; you define how correctness is measured. You co-own the eval framework with the QA Builder, writing the "ground truth" definitions that judge agent output.

Discovery

Use AI to run your own user research, synthesize support tickets, usage telemetry, and interview transcripts, along with UX research and information from Signal to help prioritize insight.

WHAT YOU'LL ACTUALLY DO

Write the mission briefs

Replace traditional PRDs with structured "Mission Specifications", agent goals, tool constraints, success evals, and failure conditions that give Builders everything they need to ship without a kickoff meeting.

Encode the business logic

Interview subject matter experts and translate their knowledge into system prompts and agentic constraints that prevent hallucinations in workflows.

Define the "ground truth"

Co-build the eval datasets and rubrics that the QA Builder uses to verify agent output against real ERP business logic; not vibes.

Rapid mission prototyping

Turn a "what if we automated X" into a working proof-of-concept prompt chain fast enough to validate before the squad commits to a build cycle.

Own the modernization backlog

Use AI-assisted analysis of usage data, support volume, and codebase complexity to continuously prioritize which legacy modules the squad attacks next based on overall strategy objectives.

THE STACK

You don't need to build it, but you need to understand it well enough to spec it precisely.

• Python (prompt scripting & eval tooling)
• SQL — ERP data fluency
• LangChain / LangGraph — agent behavior specification
• OpenAI / Anthropic APIs
• DSPy — programmatic eval frameworks
• GitHub — PR reviews & spec versioning
• Weights & Biases — embedding and eval observability

WHO YOU ARE

The "Requirements Hater"

You have a physical reaction to 40-page PRDs nobody reads. If a requirement can't be expressed as a testable agent instruction, you question whether it's real.

Agent-first thinker

You don't think in "features"; you think in "capabilities." You have already used an LLM to spec, critique, or prioritize your own work.

Domain obsessive

You find ERP business logic genuinely interesting. You understand the basics of how customer workflows work and leverage the Value Stream PM or other experts to drive why it matters and what breaks when it doesn't.

Rigor over hype

You know the difference between a compelling AI demo and an agent that's safe to run on a workflow. You won't ship the former as the latter.

WHY JOIN US

No roadmap theater

We don't do quarterly planning decks. We run missions. You own the definition of what gets built and what "done" means.

The "Final Boss" of product complexity

ERP workflows are the most logic-dense, high-stakes product surface on earth. If you can spec agents that run a supply chain for example, you have mastered the hardest problem in product.

Agentic autonomy

You won't be writing tickets for engineers. You'll be defining the missions, the evals, and the ground truth then getting out of the way.

The BUILDER Tribe

You won't be the "only AI person" in the room. You'll be 1 of 4 like-minded practitioners who are all obsessed with moving 10x faster.