Gtm Engineer, Pre-sales

Skydio Skydio · Defense · US CA San Mateo · Operations

Skydio is seeking a GTM Engineer, Pre-Sales to sit at the intersection of go-to-market teams and technical build capacity. This role involves identifying problems, designing and building AI or automation solutions, shipping them, and ensuring they scale and are adopted. The focus is on creating lasting, repeatable systems that improve the GTM machine, with an emphasis on responsible deployment and data governance.

What you'd actually do

  1. Spend time with teams across the go-to-market function to understand where the friction is and where AI or automation creates the most leverage
  2. Turn vague frustrations into concrete, buildable specs: the specific workflow, the data available, and what a better outcome looks like—not just "AI could help here"
  3. Own the full build cycle: design, build, ship, iterate—you're not a PM handing off specs, you're the person who makes it real
  4. Document and systematize what you build so knowledge lives in the org, not in your head
  5. Track outcomes: is it being used, is it saving time, is it moving the metric it was built for? Feed that back into the next round of prioritization

Skills

Required

  • Experience working with or inside go-to-market teams (sales, marketing, partnerships, deal desk, or GTM ops)
  • Understanding of how deals move, pipelines get managed, campaigns run, and team handoffs
  • Ability to have credible conversations with sales reps and engineers
  • Experience deploying AI-assisted workflows, automations, or tools
  • Technical literacy to write specs, evaluate builds, and identify AI leverage
  • Instinct to ask about scalability (10x users, data, use cases)
  • Documentation and handoff mindset
  • Ability to move fast and correct course
  • Strong prioritization skills
  • Clear, direct communication

Nice to have

  • Direct experience working with Palantir Foundry
  • Experience as an internal product manager or technical program manager for a RevOps or BizOps team
  • Hands-on experience building lightweight automations with Make, n8n, Zapier, or similar tools
  • FAA Part 107 certification

What the JD emphasized

  • AI or automation creates real leverage
  • scale
  • build things that last
  • grow
  • make the whole GTM machine better over time
  • build things that scale
  • growth in mind
  • hand off, repeat, or build on top of
  • deploy solutions responsibly
  • Drive adoption, not just delivery
  • Track outcomes
  • AI fluency
  • deployed AI-assisted workflows, automations, or tools in a real environment
  • changes daily behavior and drives real business value
  • build for scale, not just for now
  • work for 10x the users, 10x the data, or 10x the use cases
  • build with handoff in mind
  • solution that only you understand as an unfinished solution

Other signals

  • AI or automation creates real leverage
  • build it, ship it, and make sure it sticks
  • solutions that scale
  • build things that last, that grow
  • deploy solutions responsibly