GTM Engineer

Applied Compute•San Francisco, CA

7d•Onsite

About The Position

As a GTM Engineer, you’ll sit at the center of Applied Compute's commercial engine. You'll be the technical force behind our GTM motion, building the demos, agents, and automations that turn prospect conversations into signed deals. You'll run live product demos with customers, prototype bespoke agents that show what Specific Intelligence can do in their environment, and build the internal tooling that powers our sales team. This is a engineering role for someone who wants to sit at the intersection of platform and customer engagements.

Requirements

Strong engineering background with the ability to ship working prototypes fast
Hands-on fluency with modern AI tooling and frameworks, including LLM APIs, agent orchestration, evals, and the broader ecosystem of models and infrastructure
Comfort in front of customers, including technical buyers and engineering leaders, with the communication skills to translate complex capabilities into crisp demos
High agency and a bias toward shipping

Nice To Haves

Energized by switching between account research, deal support, internal tooling, and process design in the same day
Default to automation over manual operation by creating the templates, workflows, and playbooks that allow the GTM function to grow
Have a background in customer-facing work or enterprise sales, with an understanding of what it takes to support a sales motion and step in when needed

Responsibilities

Build and run customer-facing demos that translate Applied Compute's platform into tangible value for each prospect, including custom agents tailored to the buyer's domain and workflows
Prototype agents during and between customer conversations, moving from discovery call to working prototypes
Partner with our Applied AI team on active deals, owning the technical narrative in POCs and pilot scoping
Build AI-native GTM tooling that automates account research, outreach personalization, competitive intelligence, and pipeline reporting so the commercial team can move faster
Develop reference implementations, demo environments, and reusable agent patterns that accelerate every subsequent sales cycle
Bring domain fluency in the AI landscape to shape positioning and pricing conversations
Work cross-functionally with product and engineering to surface customer patterns that should become platform capabilities