GTM
Engineer – AI Infrastructure -
Remote from San Francisco, CA - $150K–$210K plus equity
About the Role
We are seeking a GTM Engineer to help drive adoption of an AI infrastructure platform used by engineering teams building production AI systems.
The role sits at the intersection of technical sales, product, growth, and solutions engineering. You will identify organisations with meaningful AI infrastructure challenges, engage directly with technical decision-makers, demonstrate the product against real customer workflows, and help convert early interest into successful pilots and long-term customers.
You should be technical enough to engage credibly with AI and ML engineers, while also being commercially minded and comfortable working directly with founders and senior stakeholders.
You will not be expected to own core product engineering, but you should be able to understand the platform deeply, run live technical demonstrations, and build lightweight prototypes, integrations, scripts, or automation where needed to accelerate customer adoption.
Key Responsibilities
Identify High-Value Prospects
Identify market segments where AI infrastructure, evaluation, reliability, or operational challenges are most acute.
Build targeted account and prospect lists.
Identify the technical and commercial stakeholders who own AI platform, ML infrastructure, agent, or production AI problems.
Use modern prospecting, CRM, automation, and AI-assisted tools to improve targeting and outreach.
Start Technical Conversations
Conduct high-quality outbound engagement through email, LinkedIn, technical communities, events, and other relevant channels.
Develop tailored outreach based on specific technical challenges rather than generic sales messaging.
Engage with Heads of AI, ML platform leaders, engineering leaders, founders, and other technical decision-makers.
Build relationships through warm introductions, community engagement, and industry events.
Run Discovery and Technical Demos
Understand how customers currently build, evaluate, deploy, and operate AI systems.
Identify technical pain points, operational cost, reliability challenges, and existing workarounds.
Translate customer requirements into relevant product use cases.
Deliver live, technically credible demonstrations tailored to the customer’s environment and workflows.
Build lightweight prototypes, scripts, integrations, or technical proof points where required.
Own Pilots and Customer Outcomes
Essential Requirements
Strong technical understanding of modern AI, machine learning, or AI infrastructure systems.
Ability to engage credibly with AI engineers, ML engineers, platform engineers, and technical leaders.
Must already be based in SF
Experience in a customer-facing technical role such as solutions engineering, technical sales, developer relations, product engineering, or technical consulting.
Strong ability to run discovery conversations and identify underlying customer problems.
Comfortable delivering live technical demonstrations.
Ability to build lightweight prototypes, scripts, integrations, or automation.
Strong written and verbal communication skills.