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GTM Engineer

140k – 175kSan Francisco, CANew York, NYGTM EngineeringHybrid
Summary

Build and deploy AI agents and automated workflows that power marketing execution, programmatic outbound, and pipeline generation at scale. Requires CS background, hands-on LLM/agent experience, and GTM intuition.

About the role

What you will do

  • Design and ship AI agents that automate marketing execution — SEM optimization, paid social content, programmatic outbound, and more
  • Build prospect-facing agentic workflows that operate at scale across email, Meta, and LinkedIn
  • Architect prompt systems, orchestration logic, and evaluation frameworks to ensure agent reliability
  • Build V0s of new growth initiatives using AI coding tools (Claude Code, Cursor), prove them with stakeholders, and partner with growth engineering to productionize
  • Apply infrastructure built by growth engineering (vector databases, agent memory, scoring models) to create applications the marketing and growth teams use daily
  • Build and maintain enrichment pipelines, lead scoring systems, and routing logic that power the marketing and growth engine
  • Find, test, and scale new intent signals and engagement triggers that deliver alpha for pipeline generation
  • Run structured experiments on agent behaviors, signals, and automation approaches — ship fast, measure, iterate or kill
  • Track the performance and ROI of what you build; use data to inform what gets scaled vs. sunset

What you will need

  • Track record of building and shipping AI-powered or automated systems in a professional role, as a founder, or through substantial side projects
  • CS degree or equivalent technical background. You understand concurrency trade-offs, system architecture, and can reason about why something is slow and how to fix it
  • Business-savvy with GTM intuition. You understand how marketing, growth, and pipeline generation work, and you have opinions on what good outbound looks like
  • Hands-on experience building with LLMs: prompt engineering, agent orchestration, evaluation loops. You've built at least one agent, even as a side project
  • AI-native. You stay at the frontier of new tools, frameworks, and agent architectures, and you bring ideas back to the team about what to integrate next
  • High agency and natural curiosity. You identify problems before anyone asks, run down rabbit holes, and experiment relentlessly
  • Knows when to use Kimi vs. Opus and why it matters
Skills
PythonLLMsPrompt EngineeringAgent OrchestrationVector DatabasesSystem ArchitectureConcurrencyAI AgentsEvaluation FrameworksLead Scoring
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