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As the first GTM Engineer at Pogo, you will partner with Growth, Sales, Design, and Engineering teams to build AI-powered systems that drive revenue. You'll operate as both a builder and operator, shipping code that directly impacts pipeline and conversion.
Key responsibilities include:
- Ship AI-powered workflows that scale growth and sales motions as a competitive advantage
- Audit the existing GTM stack, identify gaps and redundancies, and rapidly ship solutions
- 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
Pogo is an early-stage seed-funded company building an enterprise AI SaaS product. You'll work in a fast-moving environment with a culture of experimentation and "Calculated Speed"—shipping weekly rather than through lengthy processes. The company values flexibility and has implemented unlimited PTO with a minimum 20-day vacation policy. You'll sit at the center of the company, directly influencing how the GTM Engineer function develops as Pogo scales.
The role involves ambiguity and shifting priorities; you may need to build solutions in a day. The team does not yet have structured management, so you'll need to be self-directed and energized by autonomy. The company expects strong engagement and impact, though they support flexible schedules and encourage time off.
Requirements:
- 2–5 years of professional software engineering experience, with at least some applied directly 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 as polished as the product
- Systems thinking and ability to turn operational problems into clean, automated solutions
- Commercial instinct; can identify leverage from sales calls and growth dashboards
- Clear communication across technical and non-technical stakeholders, especially 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 (not just demos)
- RevOps, Marketing Ops, or Sales Engineering background before transitioning to full-time engineering
