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Salary
$140k – $220k per year
Location
In office (San Francisco)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Aug 12, 2026.

Overview
Company
Impact
Profile match
AI-powered procurement platform for hardware teams. Automate supplier management, RFQ tracking, and supply chain operations with intelligent procurement agents.

About Syntro

AI is walking, driving and flying into the physical world: humanoids, robotaxis, drones and a new class of autonomous machines. Each machine is built from thousands of parts. Sourcing just one still means trade shows, cold calls and endless scrolling on distributor sites. Supplier quotes land in a dozen formats, get re-keyed by hand into spreadsheets, and 100+ email threads follow just to confirm whether a part lands on time. It's 2026, and the most important machines of the next decade are still being sourced the way they were before the internet.

Syntro is building the first agentic procurement platform purpose-built for the realities of modern hardware manufacturing. We give manufacturers the ability to discover, select, and manage suppliers across the entire hardware lifecycle, from first prototype to production, at the speed and intelligence of AI.

We're an all-Stanford team that's experienced this problem firsthand at Apple, Dell, and Peloton. We're backed by Pear VC and Accel, alongside angels including Diane Greene (Founder, VMware) and Jeff Epstein (former CFO, Oracle).

The Role

We're looking for a founding engineer to help build the technical foundation of Syntro.

The context needed to make a procurement decision is scattered across emails, spreadsheets, ERPs, quotes, designs, and the heads of individual buyers. You'll build the systems that pull this together: giving teams visibility across their procurement operation, bringing in outside intelligence, and surfacing what needs attention next. Over time, agents will increasingly act on it directly.

This isn't a role where the architecture has already been decided and the roadmap has been broken into tickets. You'll decide how major parts of Syntro should work, build them, operate them in production, and change your mind when the first approach is wrong. You'll also help define how we build as a company: our engineering standards, infrastructure, technical decisions, and eventually the engineering team itself.

We're early enough that decisions you make now will still be visible in Syntro years from now.

What You’ll Do

  • Own systems end to end: Design, build, ship, and operate major parts of Syntro across the stack.

  • Build the intelligence layer: Turn emails, parts, BOMs, quotes, POs, supplier data, ERP records, and external information into structured context our product and agents can reason over.

  • Build reliable agents: Design systems that can reason and take action while handling uncertainty, failures, permissions, and human intervention.

  • Make foundational technical decisions: Choose architectures and abstractions that let us move quickly today without preventing us from scaling tomorrow.

  • Raise the engineering bar: Establish how we test, deploy, observe, debug, and build software as the team grows.

  • Stay close to customers: Understand how procurement actually works and use that context to make better technical and product decisions.

Who You Are

  • You're an exceptional engineer who can move comfortably across the stack.

  • You've designed and shipped complex systems from zero to one.

  • You have strong judgment about when to build something properly, when to move quickly, and when to throw something away.

  • You think deeply about reliability, data correctness, observability, and failure modes.

  • You can take an ambiguous company problem and drive it to a working system without waiting for a specification.

  • You care about the product and customer, not just the architecture.

  • You want the responsibility that comes with being one of the engineers who defines how a company builds.

  • Bonus: You've founded a company, been one of the first engineers at a startup, built production AI/agent systems, worked with large amounts of unstructured data, or built software for complex operational workflows.

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