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Netic

GTM Engineer

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
$145K – $330K a year
Posted
8 months ago

Pay and the market here

The top of this role’s range, $330K a year, is 27% above the median of $259K for engineering jobs in San Francisco (middle half $215K – $315K, 4,022 jobs that state pay).

5,003 engineering jobs open in San Francisco: 9% remote, 949 posted in the last 30 days.

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About the role

Netic is the AI revenue engine for essential services who are the backbone of the American economy. With $43M in funding from Founders Fund, Greylock, Hanabi, and Dylan Field who led our Series B, we helped our customers book hundreds of thousands of jobs across services industries in North America. There are now companies operating entirely AI-first on Netic.

You’ll join our team with relentless builders from Scale, Databricks, HRT, Meta, MIT, Stanford, and Harvard in bringing frontier AI to the physical economy, where the problems are hard, the data is complex, and the impact is immediate and tangible.

About the role

We are looking for a GTM Engineer to set the standard for how we use data and systems to not only build our own GTM engine but also help our customers build theirs.

At Netic, we currently are laying the foundation for the best GTM engine in tech. We need to build the TAM, track signals against it, choose the right set of tools to buy vs. build, set up an environment for all marketers and sellers to effectively leverage AI and much more.

For our customers, we get to do the same.

This is a perfect opportunity for the hungriest of GTM Engineers that cares about building sophisticated systems that have an outsized impact on revenue. If you’re interested, send a 2 minute video of something you’ve built to noah@netic.ai.

What you’ll do

  • Level up how we map the essential service TAM across the US
  • Come up with, test, and monitor the best intent signals against our database
  • Help inform a lot of Netic’s early tech stack
  • Build the foundational internal tools, workflows, and automations for sales and marketing at Netic to use & leverage AI to be more effective
  • Come up with ways to use GTM Engineering principles to help our customers be more successful
  • Build a flywheel based on customer conversations to accelerate our understanding of our users
  • Dig into the Netic customer usage data to inform TOF campaigns and messaging
  • Chip in wherever is needed as we scale the team

What you’ll bring

  • A background in GTM Engineering, sales, growth, RevOps or a MarketingOps role
  • Strong technical foundations – you can write some amount of code yourself and you understand how to set up the right architecture for systems that can scale
  • Great business intuition. You have demonstrated experience moving the needle on the most important metrics you have owned and choosing the right set of initiatives to focus on
  • Deep curiosity. You tinker in your free time and have demonstrated high levels of curiosity + running down rabbit holes.
  • Hustle and grit. You thrive in ambiguity, take ownership of new problems, and iterate quickly until you land what works.
  • Exceptional cross-functional skills. You build strong partnerships with Sales and internal partners to build systems that are aligned, high leverage, and easy to execute against.
  • High-ownership leader. You set the standard, lead from the front, and take full accountability for outcomes.

Our values

  1. Obsess over the customer
  2. Every second counts
  3. Sweat the details
  4. There are no blockers
  5. Be self-directed
  6. Seek and speak the truth
  7. Enjoy the ride

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

Source

Posted by Netic on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 11:18 UTC; the original is the reference.

View the original ad ↗

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