GTM Engineering grew 205% year over year in 2025. At $182K average salary, it is the fastest growing role in B2B. Here is what the role looks like, why it matters, and how to build the function at your company.
Two years ago, this role barely existed. Today, GTM Engineering is one of the most in demand specializations in B2B technology. Companies like Cursor, Webflow, Notion, and Lovable are posting GTM Engineer positions. Independent practitioners are building standalone million dollar agencies. Seven bootcamps have graduated over 2,500 students. And the role's originator, Clay, just raised $100 million at a $3.1 billion valuation to fuel the category's growth.
This is not a rebrand of an existing function. GTM Engineering represents a fundamentally new approach to revenue generation: the application of an engineering mindset to go to market systems. Rather than manually configuring CRM workflows or batch uploading CSV files, GTM Engineers design and automate the technical infrastructure that powers pipeline creation, lead enrichment, outreach personalization, and revenue intelligence at scale.
Clay CEO and co-founder Kareem Amin has called GTM Engineering "the first true AI-native profession," predicting it will become tech's next major job category. That framing matters. This is not simply operations work with a new title. It is a role born from the convergence of AI tooling, data infrastructure, and the growing technical complexity of modern revenue stacks.
Understanding where GTM Engineering came from explains why it is growing so fast now. The progression from manual operations to engineering-driven revenue systems followed a clear trajectory.
Kareem Amin founded Clay as a data integration platform. The original product focused on aggregating information across data providers, laying the foundation for what would eventually become the primary tool in the GTM Engineering stack.
RevOps emerged as a formalized function. Companies began centralizing sales ops, marketing ops, and CS ops under a single team. But RevOps roles remained primarily strategic and analytical. They built dashboards and defined processes rather than building the automated systems to execute them.
Clay formally defined the GTM Engineer title, recognizing that a new type of practitioner was emerging within their community. Co-founder Varun Anand described it: "They work within certain parameters to build scaled systems, but instead of coding software, they're coding revenue." Yash Tekriwal became widely recognized as the first person to hold the title professionally.
As Claude, GPT-4, and purpose-built AI tools matured, GTM teams suddenly had access to powerful automation capabilities. AI-powered lead scoring, automated personalization, and intelligent routing became achievable. But most marketing and sales leaders lacked the technical ability to deploy them. The demand for GTM Engineers began to accelerate.
GTM Engineering job postings grew 205% year over year. Over 2,100 active positions appeared on LinkedIn. Clay raised $100 million in Series C funding at a $3.1 billion valuation from CapitalG (Alphabet), Sequoia Capital, and Meritech Capital. Seven independent bootcamps graduated 2,500+ students. The role became a formal engineering discipline.
The GTM Engineer sits at the intersection of revenue operations, data engineering, and AI implementation. They are not sales ops professionals who learned a few tools. They are systems builders who design, construct, and maintain the automated infrastructure that generates and accelerates pipeline.
| Domain | What They Build | Tools Used |
|---|---|---|
| Data Infrastructure | Waterfall enrichment pipelines, data quality systems, lead scoring models, ICP matching algorithms | Clay, ZoomInfo, Apollo, Clearbit |
| Workflow Automation | Multi-step automation sequences, event-triggered workflows, cross-platform data syncs | n8n, Zapier, Make, custom APIs |
| AI Implementation | AI-powered research agents, personalized outreach at scale, call intelligence pipelines, autonomous prospecting | Claude, OpenAI, LangChain, custom agents |
| CRM Engineering | Custom objects, automated routing rules, lifecycle stage automation, pipeline analytics | HubSpot, Salesforce, custom integrations |
| Outreach Systems | Sequencing infrastructure, deliverability optimization, A/B testing frameworks, multichannel orchestration | Lemlist, Instantly, Outreach, Smartlead |
| Revenue Intelligence | Pipeline forecasting models, signal-based prospecting, intent data workflows, attribution systems | Gong, Clari, 6sense, Tableau |
The critical differentiator is that GTM Engineers build systems, not one-off workflows. A sales ops analyst might create a single Zapier automation to route leads. A GTM Engineer builds the entire lead lifecycle infrastructure: from initial signal detection through enrichment, scoring, routing, sequencing, and closed-loop reporting. They own the technical architecture that connects all of these tools into a cohesive revenue engine.
One of the most common points of confusion is the relationship between GTM Engineering and Revenue Operations. They are complementary but distinct functions, and conflating them leads to mis-scoped roles and poor hiring outcomes.
| Dimension | Revenue Operations | GTM Engineering |
|---|---|---|
| Primary Focus | Process optimization, reporting, strategic alignment | Building automated systems, technical infrastructure |
| Core Skills | Analytics, process design, stakeholder management | SQL, Python, API integrations, AI implementation |
| Output | Dashboards, playbooks, process documentation | Automated pipelines, enrichment systems, AI agents |
| Analogy | Business analyst for revenue teams | DevOps engineer for revenue teams |
| When to Hire | Once revenue teams exist and need alignment | Once basic ops are in place and you need scale |
The best analogy is DevOps. Just as DevOps engineers transformed how companies ship software by building the automated infrastructure between development and deployment, GTM Engineers are transforming how companies generate revenue by building the automated infrastructure between market signal and closed deal. The progression is nearly identical: what started as a community of creative practitioners is maturing into a formal engineering discipline.
Companies typically build a RevOps function first and add GTM Engineering as their go to market motion becomes more complex and the volume of automation required exceeds what traditional operations teams can manage. The two functions work best in partnership: RevOps defines the strategy and metrics, GTM Engineering builds the systems that execute against them.
An analysis of over 1,000 GTM Engineering job postings reveals clear patterns in the tools and skills that define the role. Clay appears in over 90% of practitioner profiles, making it the closest thing to a universal GTM Engineering platform. But the complete stack extends well beyond a single tool.
Clay functions as the central nervous system of the GTM Engineering stack. It connects to over 150 data providers through its waterfall enrichment model, allowing GTM Engineers to pull from multiple sources in a single workflow rather than managing separate subscriptions to each. Clay's AI agent has completed over 1.5 billion lifetime tasks across its 10,000+ customer base, which includes companies like OpenAI, Anthropic, Canva, Intercom, and Rippling.
The platform's significance goes beyond data. Clay provides the workflow canvas where GTM Engineers build their enrichment, scoring, and routing logic visually. It is to GTM Engineering what an IDE is to software development: the environment where the actual building happens.
Clay's ecosystem is a business category of its own. The company is on track to generate $50 million in revenue for its data and integration partners in 2025. Its network of 108 agencies worldwide represents hundreds of millions in collective revenue. Clay communities span 60 clubs across 30 countries, with particularly strong growth in markets like India and Pakistan.
n8n has become the preferred automation platform for GTM Engineers who need complex branching logic, self-hosted deployment, and native AI capabilities. With 70+ AI nodes and LangChain integration, it handles the multi-step workflows that simpler tools cannot. For teams that need fast implementation without engineering overhead, Zapier and Make fill complementary roles. We cover the detailed comparison in our n8n vs Zapier vs Make guide.
ZoomInfo, Apollo, LinkedIn Sales Navigator, and Clearbit provide the raw data that feeds into Clay's waterfall enrichment workflows. The GTM Engineer's job is to design the logic that determines which providers are queried in what order, how data conflicts are resolved, and how enriched records flow downstream into the CRM and sequencing tools.
Claude and OpenAI power the AI capabilities embedded throughout the stack: prospect research, email personalization, call summarization, competitive analysis, and increasingly, autonomous agent workflows that can execute multi-step processes independently. Gong and Clari provide revenue intelligence and conversation analytics that feed back into the system.
HubSpot, Salesforce, Lemlist, Instantly, and Outreach handle the customer-facing execution: CRM management, email sequencing, multichannel outreach, and pipeline tracking. The GTM Engineer ensures these tools are connected into the broader system and that data flows cleanly between them without manual intervention.
GTM Engineering separates itself from traditional operations roles because practitioners need to code. An analysis of job postings found that SQL and Python each appeared in 38% of GTM Engineer listings, meaning more than a third of companies explicitly require programming skills. Additionally, 43% of companies hiring GTM Engineers use visitor identification tools like ZoomInfo, 6sense, and Apollo, indicating that signal-based prospecting is central to the role.
| Skill | Prevalence | Application |
|---|---|---|
| Clay | 90%+ of practitioners | Waterfall enrichment, workflow design, data orchestration |
| SQL | 38% of job posts | Data querying, reporting, CRM analysis, custom integrations |
| Python | 38% of job posts | Custom automations, API integrations, data processing |
| API Integration | Growing rapidly | Connecting tools, building custom data pipelines |
| CRM Administration | Core requirement | HubSpot or Salesforce configuration, custom objects, automation |
| AI/LLM Implementation | Emerging fast | Prompt engineering, agent workflows, AI-powered research |
GTM Engineering pays like engineering, not like operations. This reflects the technical depth required and the direct revenue impact the role delivers.
The average GTM Engineer salary in the United States is $182,276 per year, according to aggregated salary data from Glassdoor and Pave. Top earners reach $329,991, with the typical range spanning $136,707 at the 25th percentile to $250,682 at the 75th percentile. This is roughly 20% above traditional sales and marketing operations roles at comparable experience levels.
| Company | GTM Engineer Salary | Context |
|---|---|---|
| Vercel | $252,000 | Highest reported GTM Engineer comp |
| OpenAI | $250,000 | AI-native company, premium comp |
| LILT AI | $221,500 | AI translation, enterprise GTM |
| Ramp | $184,000 | Fintech, high-velocity sales motion |
| Clay | $175,000 | Role originator, platform company |
Companies paying $200K+ are looking for practitioners who can orchestrate the entire revenue stack, not just operate one tool well. The premium reflects the fact that a single GTM Engineer can replace the output of multiple headcount by building systems that scale without proportional team growth.
The agency path is equally viable. GTM Engineers have built standalone million dollar agencies specializing in building these systems for multiple clients. The consulting model works because the skills are scarce, the implementation complexity is high, and the results are directly measurable in pipeline and revenue metrics.
For revenue leaders evaluating whether to invest in GTM Engineering, the decision comes down to where you sit on the maturity curve. The role makes the most sense once basic revenue operations are in place and the volume of automation required exceeds what traditional ops teams can handle.
Before hiring, catalog every manual workflow in your revenue stack. Lead enrichment, routing, sequencing, reporting, data hygiene. Quantify the hours spent on each. If your ops team is spending more than 40% of their time on manual data work and repetitive processes, you have enough surface area for a GTM Engineer to deliver immediate ROI.
Map your existing tool stack against the automation opportunities. If you are running HubSpot or Salesforce as your CRM, Clay or similar for enrichment, and any combination of sequencing tools, you have the foundation for a GTM Engineering function. The GTM Engineer will be responsible for connecting these systems and building the automated workflows between them.
The first projects should target the workflows with the highest manual effort and most measurable outcomes. Lead enrichment and scoring automation typically delivers the fastest ROI because it replaces hours of manual research with systematic data collection. Automated routing and sequencing follow closely, as they directly impact speed to lead and conversion rates. See our Complete Guide to Sales Automation for detailed workflow breakdowns.
You have two paths: hire a full time GTM Engineer or engage a specialized agency. Full time hires make sense when you have enough ongoing automation work to justify the role and when your revenue motion is complex enough to require continuous optimization. Agencies (including specialized firms like Mantyl) make sense when you need to build the initial infrastructure quickly, when your automation needs are project-based, or when you want to validate the function before committing to a full time hire.
GTM Engineering outcomes should be measured in the same terms as revenue outcomes: pipeline generated, speed to lead, enrichment coverage rates, automation coverage (percentage of workflows that are fully automated), and ultimately, revenue influenced. Build a dashboard that tracks these metrics from day one so you can demonstrate ROI and justify expanded investment in the function.
We design and implement GTM engineering systems for revenue teams. Whether you are starting from scratch or scaling an existing function, we will build the automated infrastructure that turns your tech stack into a revenue engine.
Book a Free Consultation →The trajectory of GTM Engineering mirrors what happened with DevOps over the past decade. What began as a community of practitioners bridging development and operations matured into a formal engineering discipline with standardized tools, established career paths, and dedicated budgets. GTM Engineering is on the same curve, just earlier in the timeline.
Three trends will shape the next phase. First, autonomous agents will extend the GTM Engineer's reach. Rather than building workflows that execute predefined sequences, they will build agents that can reason about prospect data, decide which actions to take, and execute multi-step research and outreach processes independently. Clay's Series C investment is explicitly funding this direction, with autonomous agents for research and messaging on the product roadmap.
Second, first-party data will become the primary competitive advantage. As third-party data commoditizes, the ability to collect, enrich, and activate proprietary signals from your own product, website, and customer base will separate high-performing GTM teams. GTM Engineers will be the ones building the infrastructure to capture and operationalize that data.
Third, the professionalization of the role will continue. By late 2025, RevOps managers, CRM admins, and data-driven GTM technologists were already taking these skills in house. As we move into 2026, GTM Engineers will be to revenue what DevOps became to software: an indispensable engineering discipline that every growth-stage company requires.
The companies that build this function now will have a structural advantage. As the tools become more powerful and AI capabilities accelerate, the gap between organizations with automated GTM infrastructure and those still running manual processes will widen. GTM Engineering is not a temporary trend. It is the operational foundation of how B2B companies will generate revenue for the foreseeable future.
Clay, "The GTM Engineering Era Begins Now," Series C Announcement, August 2025.
BusinessWire, "AI GTM Leader Clay Raises $100M Series C," August 2025.
Bloomberry, "I Analyzed 1,000 GTM Engineering Jobs: Here Is What I Learned," 2025.
Glassdoor, "GTM Engineer Average Salary and Pay Trends," 2025-2026.
FullFunnel, "The State of GTM Engineering Talent in 2025," 2025.
Crunchbase News, "AI-Powered Sales Automation Startup Clay Doubles Valuation to $3.1B," 2025.
Factors.ai, "GTM Engineering vs. RevOps: Why They're Not the Same Job," 2025.
Our team builds and manages automated revenue systems for B2B companies. We'll assess your current stack, identify the highest-impact automation opportunities, and implement the GTM engineering infrastructure to scale your pipeline.
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