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As the first GTM Engineer at Pogo, you'll partner with Growth, Sales, Design, and Engineering teams to build AI-powered systems that compound revenue. You'll work on an enterprise AI SaaS product as both a builder and operator, shipping code that directly drives pipeline and conversion.
Key responsibilities:
- Ship AI-powered workflows that scale growth and sales motions as a competitive advantage
- Audit the existing GTM stack, identify gaps and redundancies, and ship solutions rapidly
- Embed with sales and growth teams to systematize their best plays across the organization
- Build internal tools and AI agents that automate manual workflows: lead routing, enrichment, outbound personalization, account research, content distribution, and attribution
- Decide when to leverage off-the-shelf tools versus building custom solutions
- Partner closely with engineering and design to test features, provide feedback, and dogfood AI capabilities for GTM use cases
- Publish playbooks and internal guides to propagate wins across the team
The role sits at the center of the company, offering exposure to real systems with real usage that move measurable metrics. You'll work with the latest AI tools and GTM platforms, ship weekly, and get rapid feedback from end users. The company values "Calculated Speed"—iterating and shipping quickly rather than lengthy processes. This is an early-stage environment where priorities shift based on data and user feedback, and you'll be expected to run with ambiguous problems independently.
The company offers unlimited PTO with a minimum 20-day vacation policy and flexible work schedules, though the role expects more than standard hours at this stage.
Requirements:
- 2–5 years of professional software engineering experience, with direct application to GTM, growth, or revenue systems
- Heavy user of AI tools (Claude Code, Cursor, Codex) with shipped non-trivial projects
- Experience building with LLMs and AI agents (RAG, evals, tool use, prompt engineering)
- Hands-on familiarity with modern GTM stack (Clay, HubSpot, Salesforce, Apollo, Cargo, Gong, Outreach, Instantly, etc.) and fluency with APIs, webhooks, and integrations
- Strong product and design taste; internal tools should feel polished
- Systems thinking: ability to turn messy operational problems into clean, automated solutions
- Commercial instinct: can identify leverage points from sales calls and growth dashboards
- Clear communication across technical and non-technical stakeholders in ambiguous situations
- Proven track record building and maintaining production systems used by real users (internal users count)
Bonus qualifications:
- Early-stage startup experience or founder background
- Shipped AI agents that moved actual revenue metrics
- RevOps, Marketing Ops, or Sales Engineering background before transitioning to engineering
