Full-time • San Francisco, NYC, or somewhere in the Midwest (US) • Light travel optional

At Endeavor, we’re rebuilding ERP from first principles for $1B+ manufacturing and distribution companies. These are the real-world operators who keep supply chains moving and the economy running, and they’re buried under decades of legacy software and brittle processes.

We’re deploying agentic systems that automate high-friction back-office tasks like sales order entry and procurement. Our AI stack plans, reasons, and acts. Your job is to build the scaffolding that makes all of that possible.

This role sits at the intersection of backend engineering, AI agent design, and real-world system integration. You’ll translate abstract agent behaviors into crisp APIs, scale data flows across legacy ERP boundaries, and help architect the product’s core backend infrastructure as we scale.

What You’ll Do

• Design and build the backbone of our agentic ERP: APIs, task runners, state managers, data flows, observability

• Work closely with Applied AI Researchers to turn reasoning patterns into infrastructure that’s fast, robust, scalable, and debuggable

• Collaborate with Forward Deployed Engineers to ship modules into production within chaotic, real-world ERP environments

• Architect interfaces between LLM agents and structured systems (databases, CRMs, procurement software)

• Define and evolve foundational abstractions that support AI workflows, retries, context, and memory

• Help us scale the platform from early customer deployments to a durable enterprise product
  

You Might Be a Fit If You

• Have 3–10 years of experience building backend systems in fast-moving environments

• Have been through Series A → scale at a startup, and want to do it again

• Love working with both researchers and customer-facing engineers, and know how to translate between them

• Write clean code, design clean systems, and know where to cut corners without leaving a mess

• Have a sixth sense for debugging distributed workflows and strange edge cases

• Think in terms of interfaces and invariants

• Want to work on something where the stakes are high and the feedback loops are tight
  

Bonus Points

• You’ve built infra to support AI/LLM workflows

• You’ve worked in legacy-heavy domains (e.g. healthcare, industrial, govtech)

• You’ve designed systems for agents, workflows, retries, or task graphs

• You’ve done serious systems work, but still like explaining your code to others