Introduction
GTM Engineering focuses on creating and optimizing the systems and processes that support a company's go-to-market strategy. This involves designing infrastructure, conducting experiments to identify scalable solutions, and embedding successful approaches into the organization's tools and workflows. The GTM Engineer is the one who puts everything togheter and that's a role that basically originated with Clay. As one would imagine, the initial GTM pioneers are former employees of Clay. The company has published a detailed article that provides valuable insights into what a GTM Engineer entails:
They'll develop deep expertise in modern sales technology - knowing when to use AI vs. human touch, creating automated data pipelines for prospect information, and continuously measuring and optimizing their systems for better performance.
In my own words: it’s the sales professional whose only job is to generate more pipeline without increasing the headcount - and the headcount that is going to suffer is the SDR. Traditionally, the sales framework consists of four roles:
- SDRs research prospects and send outbound emails;
- Account Executives (AEs) handle calls and close deals;
- Sales Engineers provide technical explanations of the product; and
- Revenue Operations (RevOps) ensure the CRM and tools function smoothly.
A new role, the GTM Engineer, is emerging to optimize the Lead Generation process, enhancing SDR productivity. This means SDRs will no longer need to craft personalized emails. Cold Calls can also be optimized as Clay automates Lead Qualification, allowing SDRs to focus only on high-quality leads (scoring 8 or above).
GTM Engineers vs SDR Teams
Aamir Bajwa, founder of Corebits, highlighted in a LinkedIn post the cost comparison for Lead Generation between employing one GTM Engineer versus a team of five SDRs. His analysis shows that a GTM Engineer using an effective Clay outbound engine can reach 10,000 prospects per month. Considering the salary for one GTM Engineer and software expenses, the Cost per Acquisition (CPA) is USD $357. In contrast, a team of five SDRs results in a CPA of USD $600, leading to an estimated Customer Acquisition Cost that is USD $20,000 higher on a monthly basis.
Patrick Spychalski created a LinkedIn Post expressing the same ideas:
Instead of hiring five SDRs to handle research, enrichment, and outreach, one person can now run that entire motion as a workflow. Use job change or hiring signals to surface leads, enrich with Clay + LinkedIn + Clearbit, pull in tech stack and intent data, and push to Apollo or Instantly for automated outreach. The pipeline refreshes daily - no manual work required. In 2025, the teams that win won’t be the ones who hire the most - they’ll be the ones who build the best systems.
New Tendencies for the GTM Role
The role of SDRs (Sales Development Representatives) is not expected to become completely obsolete, but their numbers are likely to decline. As with many professions, the advancement of AI will render certain aspects of the SDR role unnecessary. In the near future, I anticipate a significant shift, with many SDRs transitioning into roles as GTM (Go-To-Market) Engineers. There will likely be an increased emphasis on “tech-savy” sales professionals rather than empathy and communication-based soft skills.
Now, you will be surprised with what I am about to say:
As of the date this article was published, there were only 581 GTM Engineers globally (based on a LinkedIn Sales Navigator search). Yes, globally - not just in Silicon Valley, where, even then, that number would be remarkably low.
It seems people did not yet understand what is going on.
One year from now, I plan to conduct this search again out of curiosity to see how these numbers evolve. If you'd like to make a prediction, feel free to share your estimate in the comments section.
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Some people are understanding quite well what is going on though. The concept of GTM Engineering appears to be gaining traction across various companies as they adapt to evolving business strategies and operational needs. Snyk is rebranding one of its teams to emphasize this focus, calling it “GTM Engineering.” OpenAI already includes GTM Engineers in its structure, while Dropbox has appointed a Head of GTM Engineering, signaling its importance within the organization. Additionally, many other companies are actively seeking GTM Engineers, highlighting the growing recognition of this role in driving go-to-market success.
Example of a GTM job openings at SEMRush:
Other AI Roles Beyond GTM Engineering
In August 2025, the Claymation blog highlighted the rise of a new AI-Native workforce, which has started to emerge following the GTM (Go-To-Market) phase. This development is attributed to the natural evolution of Clay and other advanced AI tools. The blog, now under Clay's ownership after its acquisition for USD $1 million in early 2025, explores how these tools are reshaping industries and redefining traditional workforce structures.
The GTM Engineer was the first sign of an AI-native knowledge worker. But as AI agents become more sophisticated, we're seeing an evolution beyond this initial role. The future workforce isn't just adapting to AI; it's being built around it. These roles are just the beginning. The next wave of specialized, AI-native positions will drive business growth and operational efficiency in ways we haven't seen before
Here are some of the new roles we can expect to see emerge:
- GTM Agent Builders: Experts in designing, training, and deploying AI agents to execute specific go-to-market strategies.
- Agent Managers: The conductors of the AI orchestra, responsible for overseeing and optimizing the performance of multiple AI agents across an organization.
- Prompt Engineers: Specialists who craft highly effective prompts to guide AI agents toward desired outcomes, ensuring precision and quality.
- Generative Engine Optimization (GEO) Managers: Professionals focused on optimizing content and campaigns specifically for generative AI platforms.
- Answer Engine Optimization (AEO) Managers: Experts who ensure a company's information is discoverable and accurately represented within new AI-powered "answer engines."
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