GTM engineer: salary, jobs and how to hire one

The title itself. Counted from the list above, on the boards we read on November 14, 2026: 7 open roles have GTM engineer in the title, at 4 companies. Clay lists the most, with 4 of the 7. Of the 7 open roles, 7 name New York as a location, none are listed as remote and none are based somewhere else. By level, read from the title alone: Mid 6, Manager 1; a title with no level word counts as Mid.

Posted pay. The 7 New York postings among them carry 6 distinct annual base ranges: too few postings to publish a band. Our floor is 8. We count base salaries the companies wrote on New York postings, once per distinct range at a company, and leave out on-target earnings and equity. Until there are enough, the function-wide bands in the pay section below are the reference.

How long they have been open. Of the 7 openings we can date, the median has been up 57 days. 1 was first recorded in the last 30 days, and 1 has been up for more than 90. We date an opening from the day our daily snapshot first recorded it (role tracking began on August 15, 2026), and a role reposted under a new link starts over. A posting that comes down has closed; that is not evidence that anyone was hired.

What the postings name. Terms named in the text of these postings, with the number of the 4 companies naming each. We track AI and data tooling, not CRMs, enrichment or sequencing products, so this is the engineering half of what the postings ask for.

• AI agents 3
• Data pipelines 3
• SQL 3
• LLMs 2
• Python 2

The titles next door

The same boards carry 26 openings with revenue operations, sales or marketing operations, revenue systems or GTM systems in the title, at AlphaSense, Clay, EliseAI, Rogo and 9 others. Level, read from the title: Mid 8, Director 5, Manager 4, Senior 4, Leadership 2, Staff/Principal 2. These are the seats the role grew out of and the ones it works beside. Whether a company calls the builder a GTM engineer or a GTM systems lead is a naming choice, so search both.

The function the systems serve

By our title rules, 501 open roles (34% of the 1,486 on these boards) are go-to-market titles: sales, marketing, customer success, partnerships and solutions. They are open at 36 companies. Of the 501 open roles, 253 name New York as a location, 77 are listed as remote and 171 are based somewhere else. By level: Mid 317, Senior 75, Manager 39, Director 32, Leadership 17, Entry 13, Staff/Principal 8. The full list is on the go-to-market jobs page.

This is the team a GTM engineer builds for, and its size is the headcount the role’s systems are judged against. Of the 501 openings we can date, the median has been up 58 days. 164 were first recorded in the last 30 days, and 179 have been up for more than 90.

AI and data terms named in go-to-market postings, with the number of companies naming each (of 36 companies with a go-to-market opening). A term here is one that someone in a go-to-market seat is being asked to know, and those people are the users of whatever a GTM engineer builds.

• SQL 15
• AI agents 12
• LLMs 8
• Generative AI 5
• Python 5
• Machine learning 4
• OpenAI 4
• TypeScript 4
• Data pipelines 3
• AI safety 2

On August 15, 2026, the first day we kept this count, the daily snapshot recorded 529 go-to-market postings across the 48 companies read that day. On November 14, 2026 it recorded 501 go-to-market postings across the 47 companies read that day. Across the 92 daily snapshots from then to now, the count ran from a low of 494 to a high of 559. The set of companies we read changes over time, so these are two counts, not a growth rate. Changes measured on the same companies at both dates are in the NYC AI Hiring Index.

Published 2026 compensation guides converge on roughly $100k–130k entry, $130k–180k mid-level, and $180k–250k+ senior, with staff-level builders above that — and Clay itself reported as the title’s top-paying employer. That is engineering-tier pay for a role most companies budget out of sales — which tells you how much leverage they believe it carries. Those are national guides; what New York AI companies write on their own postings is on this page too.

The negotiation wrinkle unique to this role: structure varies wildly. Some companies band GTM engineers with engineering (high base, standard equity); others treat them as revenue roles with meaningful variable comp tied to pipeline. Neither is wrong, but they are not comparable at face value — get the fixed/variable split and the measurement definition in writing. The general playbook is in Neuronify’s salary negotiation guide.

There is also a third path the salary guides miss: independent. Because a GTM engineer’s output is directly measurable in pipeline, the role converts to fractional and agency work faster than almost any technical specialty — a builder running outbound systems for three or four clients can out-earn the senior band, and the Clay-certified agency ecosystem exists precisely because demand outruns full-time supply. The economics of going independent are covered in Neuronify’s freelance guide and rate calculator.

Hire for a system, not a title. Decide which outcome the first 90 days should produce: inbound leads routed to a rep in minutes, a signal-based outbound motion, a clean enrichment pipeline, or the CRM reporting that tells you which of them works. That outcome shapes the job description, the interview and the comp plan.

Evaluate with a work sample. The strongest signal is a short, paid exercise on your own data: build a small enrichment and scoring workflow for fifty target accounts, or design the routing for your demo-request form. Pair it with one question every strong candidate can answer in detail: what is a system you shipped, and what did it produce in meetings, pipeline or cost per qualified account?

Look for restraint as well as skill. Every automation should ship with a metric, because an unmeasured workflow is noise at scale. And a system that sends a thousand mediocre emails is a brand-damage machine with good throughput. Candidates who can explain what they chose not to automate usually have the judgment you are paying for.

Decide on full time versus outside help. A full-time hire makes sense when there is a steady backlog of systems to build and maintain. If you need the first systems live quickly, or want to prove the return before adding headcount, a vetted independent builder or agency is often the faster start. The general process for technical hires is in Neuronify’s guide to hiring AI engineers.