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Salary
$90k – $130k per year
Location
In office (Hoboken)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 27, 2026.

Overview
Company
Impact
Profile match
GUILD is an AI-native defense contractor that turns government requirements into manufactured aerospace parts, from planning through delivery.
Backed by Y Combinator

About GUILD

GUILD is building the Amazon for defense manufacturing. We're an AI-native defense prime: we win government contracts, route production across our network of vetted US factories, handle compliance, and deliver straight to the government's door.

Lockheed, Boeing, RTX and the rest of the primes are slow and expensive, and a broken procurement system protects them. Meanwhile the defense industrial base has shrunk 40%. The government pays too much, waits too long, and has nowhere else to go. We're here to beat the primes at their own game and fix how the government builds what the country needs.

We have won nearly $300K in DoD contracts in the last few months to manufacture fighter jet components for the Air Force. Today we make aerospace parts. Next we'll run our own automated factory and full defense programs.

We're backed by Y Combinator (S26), Rebel Fund, Pioneer Fund, Twenty Two Ventures, and others.

The role

You'll be GUILD's first engineering hire. Both founders write code today, and you'll build alongside us and own major parts of the platform.

You won't be starting from a blank page. Our platform is already running on live DoD work, and your job is to make it faster, smarter, and more reliable every week.

This is not a software-only job. Some weeks you'll be improving the agents that parse government technical data packages. Other weeks you'll be on the factory floor running 3D printers, working with a CNC machine, or redesigning a fixture.

What you'll build and improve

  • Technical data package ingestion: extend the agents that turn government drawings and specs into full bills of materials, raw material requirements, and compliance flowdowns

  • Production routing: improve the systems that split work across our factory network to minimize cost and lead time

  • The data layer: own and scale the database and pipelines that power the platform

  • 3D printing factory operations: help run and automate our additive manufacturing operations, from print planning and machine utilization to quality control and throughput

  • Hardware: CAD/CAM, CNC, and tooling as we build toward our own automated factory

Your first 90 days

  • Week 1: Ship an improvement to our existing platform that's used on live DoD work.

  • Month 1: Spend time in our 3D printing operations and with partner factories, find the biggest bottleneck in how parts get made and routed, and build the fix.

  • Month 3: Own a major piece of the platform end to end and help shape our in-house manufacturing capability.

Must-haves

  • US citizen (required for our defense work)

  • 2-3+ years of engineering experience in industry

  • Strong TypeScript and Python
  • Deep database and SQL expertise. Schema design, query performance, and data modeling come naturally to you.

  • AI-pilled. You build with LLMs every day and have hands-on experience with harness engineering, frontier model providers, and open-source models.

  • Ready to get your hands dirty with hardware, 3D printing, and electrical and mechanical engineering

  • In person in Hoboken, NJ, 4-5 days a week

Nice to have

  • CAD/CAM, CNC, or additive manufacturing / 3D printing experience (very valuable here)
  • Prior startup experience, especially as an early or founding engineer
  • AWS, Supabase, or Google Cloud
  • Background in aerospace, defense, manufacturing, or supply chain
  • Eligibility for a security clearance

You don't need defense experience. Government procurement is opaque and full of acronyms, and nobody walks in knowing it. We'll teach you.

Founders

  • Kaya Celebi (CEO): ML researcher. Former AI Tech Lead at Hartree Partners (commodities hedge fund) and ML Engineer at Morgan Stanley. MS in CS from Columbia, BS in CS and Statistics from Duke.

  • Erim Gurlemis (COO): Grew up on his family's factory floor, then worked in Morgan Stanley's Global Investment Office. BA from Rutgers.

  • We met at Morgan Stanley. We both come from military families, and this mission is personal for us.

Location

Our office is in Hoboken, NJ. We're expanding in the next few months, likely in Hoboken or Manhattan. You'll also spend time on the factory floor and at partner factories.

Compensation

  • $90,000-$130,000 salary
  • 0.5-2% equity
  • Health benefits and a commuter stipend

The real upside is joining as the first engineer at a company setting out to beat Lockheed and Boeing.

Interview process

  • 30-minute call with Kaya. Background, motivation, and fit.

  • 60-minute technical interview. Some simple live coding, then ambiguous, real-world problem solving and system design. Expect to reason through a messy problem the way you would on the job.

  • 30-minute conversation with Erim and Kaya. You'll get a decision right after.

  • 30-minute call with Kaya (background, motivation, fit)
  • 60-minute technical interview: some simple live coding, then ambiguous real-world problem solving and system design
  • 30-minute conversation with Erim and Kaya, followed by a decision
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