Three years ago the job title did not exist. Today there are 739 open postings for it, the median US package is $160,000, and the single most requested tool is not Salesforce.
We read all 739 postings and turned them into a report.
The GTM Engineering Jobs Report is a free, ungated industry study of what companies are actually hiring for when they hire a GTM Engineer. Not opinions from LinkedIn. Job descriptions, counted.
This article covers the findings that matter most, whether you are hiring for the role, moving into it, or deciding if you need it at all.
What you will find in this article
- A working definition of GTM Engineering, and how it differs from RevOps and growth
- The tool stack, ranked by how often each platform appears in postings
- Why 86% of these roles require AI skills, and which model gets named more
- What the role pays in the US, with the full salary distribution
- Who is hiring, where, and why the demand is so fragmented
- The build-versus-hire question, answered with numbers
Methodology in one paragraph
Everything below comes from 739 real GTM Engineer job postings. Of those, 584 included a full description, which forms the base for tool, skill, and responsibility percentages. Sixty-three US roles disclosed a salary range, which forms the pay base. Percentages are the share of postings that mention a given item.
What is a GTM Engineer?
A GTM Engineer builds and automates the go-to-market stack with code, data, and AI. They sit between sales, marketing, and engineering, and they own the systems that turn raw data into pipeline. The work is workflow automation, data enrichment, outbound infrastructure, and reporting.
The clearest signal comes from the responsibilities data. Workflow automation appears in 83.7% of postings, lead and data enrichment in 64.9%, outbound automation in 60.8%, and reporting in 57%. Those four duties define the job.
Here is how the role compares to the ones it gets confused with:
Four roles that get put in the same job ad
Clay
n8n
APIs
The distinction that matters: RevOps keeps the system of record clean. A GTM Engineer builds the system of action on top of it.
The stack: Clay outranks every CRM
This is the finding that surprises people most. A platform barely three years old is now required more often than Salesforce or HubSpot.
Clay shows up in more postings than Salesforce
| Tool | Share of postings | Count | |
|---|---|---|---|
| Clay | 60.4% | 353 | |
 HubSpot | 51.9% | 303 | |
 Salesforce | 48.1% | 281 | |
 Outreach | 45.0% | 263 | |
| n8n | 35.8% | 209 | |
 Zapier | 32.5% | 190 | |
 Apollo | 24.0% | 140 | |
 Instantly | 15.2% | 89 | |
 Smartlead | 13.2% | 77 | |
 Gong | 11.8% | 69 | |
 Snowflake | 9.1% | 53 | |
 ZoomInfo | 8.2% | 48 |
The long tail runs Lemlist at 6.5%, Segment at 5.8%, dbt and Looker at 5.7%, Marketo at 5.3%, Salesloft at 4.8%, and 6sense at 4.5%.
Three reads on this table.
The center of gravity moved. Clay at 60% ahead of Salesforce at 48% means companies now hire for the tool that acts on data, not the tool that stores it.
Automation beats analytics. Clay plus n8n at 36% and Zapier at 33% forms the modern backbone. Every warehouse and BI tool sits below them.
Sending engines are core infrastructure. Outreach at 45%, Instantly at 15%, Smartlead at 13%, and Lemlist at 6.5% put outbound execution inside the engineering remit rather than next to it.
If you are writing a job spec, name the tools. If you are preparing for interviews, learn Clay first.
This is an AI-native role, and the model split is interesting
AI or LLM skills appear in 86.3% of postings, which is 504 of the 584 described roles. Almost half, 49%, explicitly ask the candidate to build AI agents.
Below that headline the requirements get specific. Anthropic's Claude is named in 32.7% of postings and OpenAI's GPT in 21.7%. Prompt engineering shows up in 11.6%, AI-assisted coding tools like Cursor in 10.1%, and vector databases or RAG in just 3.6%.
Two things stand out. Claude beats GPT by 11 points, and in a sample dominated by AI-native startups that gap says something about which model this cohort builds on by default. And RAG at under 4% confirms the shape of the work. These teams are wiring models into workflows, not building retrieval infrastructure.
AI fluency has stopped being a differentiator in this role. It is the entry ticket.
The technical bar: glue code, not greenfield software
The role is genuinely technical, but the work is wiring systems together rather than building products from scratch.
On the technical side, API and webhook fluency leads at 65.9%, followed by Python at 40.6%, SQL at 35.4%, JavaScript or TypeScript at 28.1%, ETL and pipelines at 21.9%, and no-code tools at 15.9%.
Postings screen just as hard on how you operate. A builder or scrappy mindset appears in 67.6% of them, ownership in 50.9%, analytical thinking in 49.5%, cross-functional work in 47.8%, experimentation in 41.4%, and communication in 26.5%.
Put those two lists together and you get the archetype the market is buying: a scrappy builder who owns outcomes, works from data, and moves across sales, marketing, and engineering without needing a translator.
Notice what is missing. Nobody is asking for computer science degrees, system design interviews, or production-grade software engineering. API fluency at 66% matters more than Python at 41%.
What a GTM Engineer earns in the US?
Across 63 US postings with a disclosed range, the median total-comp midpoint is $160,000, with a typical band of $130,000 to $180,500. That works out to roughly $13,300 per month.
The spread is wider than the median suggests. At the 25th percentile, postings advertise $110,000 to $170,000. At the 75th, $145,000 to $200,000. The floor of the market sits at $50,000 to $80,000 and the ceiling at $210,000 to $250,000.
The mean midpoint lands at about $153,000, slightly below the median, which tells you the bottom of the market pulls the average down more than the top pulls it up.
The best-paying offers cluster at AI infrastructure and developer-tools companies. DISQO tops the sample with a Principal GTM Engineer role at $210,000 to $235,000. Mutiny, Cresta, Harper, and LiveKit all advertise bands topping out between $230,000 and $250,000. WorkOS and Baseten both post $175,000 to $200,000, and Confido pays $170,000 to $210,000 for a founding hire.
Budget honestly. If you post a $110,000 range in San Francisco, you are competing for candidates against companies offering double at the top of the band.
Where the jobs are, and who is hiring
Forty-three percent of demand sits in the United States, led by San Francisco and New York.
That is 321 of the 739 postings. India follows at 8%, Germany at 7%, the UK at 6%, and Canada at 4%. France, Spain, and Poland each hold around 2%, with the remaining quarter spread across everywhere else.
Top cities across the sample: San Francisco, New York, London, Bengaluru, Berlin, and Paris.
The hiring pattern matters more than the geography. Equinix leads with 16 postings, followed by Rollstack at 9 and Clay at 8. After that it collapses into a long tail of hundreds of companies hiring one or two people each.
Clay is hiring 8 GTM Engineers for itself. The company that built the category's defining tool is also one of its biggest employers.
That fragmentation is the real signal. A category dominated by a few large buyers is a niche. A category adopted one hire at a time across hundreds of companies is a shift.
Nobody is hiring juniors
Title and seniority data explain why this role is hard to fill.
Most postings use the plain title. GTM Engineer accounts for 437 of them, with AI GTM Engineer next at 84 and senior, staff, or lead variants at 72. Below that sit GTM or RevOps Ops Engineer at 40, Founding GTM Engineer at 35, GTM Automation Engineer at 21, Growth Marketing Engineer at 20, and GTM Systems Engineer at 18.
On seniority, 621 postings are mid-level or unspecified, 74 are senior and above, 35 are founding roles, and just 10 are junior.
Thirty-five companies are hiring a Founding GTM Engineer, meaning employee number 1 to 10, brought in to build the revenue machine from scratch.
Ten junior roles across 739 postings tells you the market wants people who have already done this. There is no training pipeline for a discipline that is three years old, which is exactly why the salaries look the way they do.
Should you hire one, or build the system another way?
Run the arithmetic before you open the req.
A US GTM Engineer at the median costs $160,000 in total comp. Add payroll overhead, and add the stack they will ask for on day one. Clay, a sequencer, an enrichment waterfall, and data credits realistically add $2,000 to $5,000 per month.
So the first year runs $200,000 or more, before the role produces anything.
Then add the risks the data exposes:
- Ten junior roles in the whole sample. You are hiring from a pool of people who already have the skills, and they have options.
- The archetype is scarce. A scrappy builder who is technical, analytical, and cross-functional is the rarest profile in ops hiring.
- Ramp is real. The person has to learn your data, your ICP, and your stack before the first automation ships.
- Key-person risk. One person holds the whole system. When they leave, the automations stay and the knowledge goes.
Hiring is the correct answer when GTM engineering becomes a permanent, strategic function inside your company. Most companies are not there yet, and they need pipeline this quarter.
At Vanderbuild we act as the external GTM engineering team. We have run 250+ campaigns and built 50+ revenue engines, with a 41.3% response rate on our best-performing campaigns. We build the exact stack this report describes, so the machine runs without you competing for a scarce hire.
How to write a GTM Engineer job description that works?
If you are hiring, the data gives you the spec.
- Name the tools. Clay, n8n or Zapier, your CRM, your sequencer. Candidates filter on tool names, not on adjectives.
- State the AI expectation clearly. Half the market asks for agent-building. Say whether you do.
- Lead with the four core duties. Workflow automation, enrichment, outbound automation, reporting. That is the job.
- Set the technical bar at APIs, not at Python. API and webhook fluency appears in 66% of postings and screens better than a language requirement.
- Disclose the range. In a market where 63 postings publish salary and the median is $160,000, hiding your band signals that it is below it.
- Do not write it as junior. Ten junior postings exist across the entire sample. Pricing the role below the market gets you nothing but silence.
FAQ: GTM Engineering
What does a GTM Engineer do? They automate go-to-market workflows, enrich the data feeding those workflows, run outbound infrastructure at scale, and report on the results. Those four duties appear in the majority of all postings analyzed.
What is the average GTM Engineer salary? Across 63 US postings with disclosed pay, the median total-comp midpoint is $160,000, with a typical band of $130,000 to $180,500. The top of the market reaches $250,000 at AI-native startups.
What tools does a GTM Engineer need to know? Clay first, named in 60.4% of postings. Then HubSpot at 51.9%, Salesforce at 48.1%, Outreach at 45%, n8n at 35.8%, and Zapier at 32.5%.
Do you need to code to be a GTM Engineer? Some. API and webhook fluency appears in 65.9% of postings, Python in 40.6%, and SQL in 35.4%. The work is connecting systems rather than building software from scratch.
Is GTM Engineering the same as RevOps? No. RevOps owns process, forecasting, and the system of record. GTM Engineering owns the automated systems built on top of it. Forty postings blend the two titles, so the boundary is still moving.
What is a Founding GTM Engineer? An early hire, typically employee 1 to 10, brought in to build a company's entire go-to-market machine from scratch. Thirty-five such roles appear in this sample.
How do I become a GTM Engineer? Learn Clay, then automation with n8n or Zapier, then APIs and webhooks. Build and document real workflows. With only 10 junior postings in the sample, a portfolio of shipped systems matters more than a title.
Is the report free? Yes. No gate, no form, no email required.
Ten numbers to remember
- 60% of postings require Clay, ahead of both Salesforce and HubSpot.
- 86% require AI or LLM skills, and 49% want the candidate to build AI agents.
- Claude at 33% beats GPT at 22% in named model requirements.
- 66% need API and webhook fluency, 41% Python, 35% SQL.
- 84% name workflow automation as a duty, then enrichment at 65%.
- $160,000 is the US median total comp, in a band of $130,000 to $180,500.
- $250,000 is the top of the best-paying band, at AI-native startups.
- 43% of demand is in the US, with Europe and India next.
- Hundreds of companies hiring one or two people each, the signature of a new category.
- 35 Founding GTM Engineer roles, and only 10 junior roles in the entire sample.
The role is real, the pay is set, and the talent pool is thin. That combination is why most companies will end up buying this capability before they manage to hire it.
Want the machine built instead of the job posted? Book a GTM audit.
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