Gtm Engineer

Airtable Airtable · Enterprise · New York, NY +1 · Revenue Operations

GTM Engineer at Airtable to build and automate go-to-market workflows using AI agents, LLMs, and no-code/low-code tools. The role involves developing AI-powered systems for outbound, enrichment, and account research, connecting GTM data flows, and treating systems as products. Requires experience with automation platforms, Salesforce, APIs, and a strong understanding of AI and modern GTM tooling.

What you'd actually do

  1. Automate manual GTM processes end-to-end, from lead enrichment and account research to pipeline hygiene and outbound sequencing, using AI agents, no-code/low-code tools, and custom integrations.
  2. Leverage LLMs (Claude, ChatGPT, Gemini) to build intelligent automations for outbound, enrichment, account research, and internal workflows.
  3. Keep clean, reliable data moving between core GTM systems — Salesforce, Databricks, enrichment tools, and downstream platforms like Gong and Outreach.
  4. Treat the systems you build as products: gather feedback, iterate on what's working, and proactively identify what to build next.
  5. Partner with Sales, Marketing, and RevOps to understand how work actually gets done, then build tools that make it dramatically better.

Skills

Required

  • 3-5 years of experience in GTM engineering, revenue technology, data engineering, or a closely related technical domain.
  • Hands-on experience with workflow automation platforms (Zapier, n8n, Clay, or similar).
  • Familiarity with Salesforce.
  • Experience connecting systems via APIs
  • Follow the AI space closely and have already built workflows with LLMs (Claude, ChatGPT, Gemini)

Nice to have

  • Experience with Databricks or other data warehouses (Snowflake, BigQuery).
  • Familiarity with Hightouch (reverse ETL) or Fivetran (data pipelines).
  • Background in software engineering, data engineering, or a technical IC role.
  • Basic scripting in Python or JavaScript for custom workflow logic.
  • Experience using Airtable as an operational platform or data layer.
  • Prior experience in a high-growth or startup environment building foundational systems from scratch.

What the JD emphasized

  • AI agents
  • AI-native GTM tooling
  • LLMs

Other signals

  • Leverage LLMs to build intelligent automations
  • Stay at the frontier of AI-native GTM tooling
  • Build and Automate GTM Workflows using AI agents