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Nango

GTM Engineer (Founding)

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
$150K – $225K a year
Posted
7 days ago

About the role

Nango (YC W23) connects AI agents to the 1,000+ systems where work happens, providing a critical connectivity layer for the AI stack.

Nango serves 700+ paying customers, including ServiceNow and Replit. We’re a YC-backed team of 20 from AWS, GitHub, Okta, Snyk, and other leading tech companies.

We’re hiring our first GTM Engineer to turn market pull into scalable growth across the customer journey—from ads and the website to onboarding, product experiments, and growth features.

What You’ll Do

  • Build experiments across acquisition, onboarding, and activation.
  • Improve our website, signup flow, and product onboarding.
  • Own instrumentation, attribution, and funnel analysis.
  • Build lead scoring, enrichment, and sales automation.
  • Connect product usage with marketing and sales systems.
  • Launch new channels across ads, marketplaces, and product-led loops.
  • Ship growth-oriented product features end-to-end.
  • Turn successful experiments into reliable systems.

Who You Are

  • You are a pragmatic full-stack engineer who can ship independently.
  • You are comfortable with TypeScript, modern web applications, APIs, and data.
  • You are curious about customers, positioning, marketing, and sales.
  • You care about copy, UX, conversion, and business outcomes.
  • You use data to form hypotheses and evaluate results.
  • You think in systems rather than one-off scripts.
  • You move quickly and create structure without waiting for a playbook.
  • Bonus: you have worked in growth engineering, GTM engineering, technical RevOps, or founded a product.
  • Bonus: you have experience with developer tools, B2B SaaS, or AI products.

Location

This is an in-person role in San Francisco.

Source

Posted by Nango on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 00:27 UTC; the original is the reference.

View the original ad ↗

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