GTM Engineer, Pre-Sales

Skydio•San Mateo, CA

11d•$103,500 - $140,000•Hybrid

About The Position

As our GTM Engineer, Pre-Sales, you sit at the intersection of our go-to-market teams and our technical build capacity. You understand how various go-to-market teams operate—what slows them down, what they actually need, and where AI or automation creates real leverage. You own the full cycle: find the problem, design the solution, build it, ship it, and make sure it sticks. This is a high-impact role. The work you do here won't just help one team move faster—it will reshape how Skydio goes to market. That means the bar isn't just "does it work"—it's "does it scale." A one-off fix that doesn't compound, a workflow that breaks under volume, a tool only one person knows how to use—these aren't wins. You build things that last, that grow, and that make the whole GTM machine better over time. You move fast. You prioritize ruthlessly. And you never ship something you can't hand off, repeat, or build on top of.

Requirements

You understand how GTM teams work: You've spent meaningful time working with or inside go-to-market teams—sales, marketing, partnerships, deal desk, or GTM ops. The title matters less than the exposure.
You understand how deals move, how pipelines get managed, how campaigns run, and where the handoffs between teams create friction or opportunity.
You can have a credible conversation with a sales rep about what slows them down, and a separate credible conversation with an engineer about what data is available and what a workflow needs to do.
You're a builder with AI fluency: You've deployed AI-assisted workflows, automations, or tools in a real environment—you know the difference between a demo that looks impressive and something that changes daily behavior and drives real business value.
Technically literate enough to write a real spec, evaluate a build, and spot where AI can drive real business leverage.
You build for scale, not just for now: You instinctively ask "what happens when this needs to work for 10x the users, 10x the data, or 10x the use cases?" before you start building.
You document as you go, build with handoff in mind, and treat a solution that only you understand as an unfinished solution.
You know the difference between a fast prototype and a durable system—and you're intentional about which one you're building and when to make the transition.
You've got the right instincts: You default to action: you move fast, don't wait for perfect information, and you're comfortable being wrong fast and correcting course.
Strong prioritizer—you understand the bottleneck is build capacity, not ideas, and you take that responsibility seriously.
Clear, direct communicator who can translate between the vocabulary of GTM and the vocabulary of engineering without losing either audience.

Nice To Haves

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
Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged for all Skydio employees and required for certain positions.

Responsibilities

Find the right problems to solve: 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.
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".
Evaluate opportunities not just by impact, but by scalability—a solution that works for one rep or one campaign isn't worth building; a solution that works across the org is.
Maintain and prioritize a backlog so we're always working on the highest-leverage problems, not the loudest requests.
Build things that scale: 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.
Design every solution with growth in mind—it needs to hold up as the team, the data, and the use cases expand. You build for the future while remaining nimble.
Avoid one-off fixes: if a solution can't be handed off, repeated, or built on top of, it's not done.
Use the right tool for the job—lightweight automations with n8n, Zapier, or Clay for speed; more robust architectures when the problem demands it—and be deliberate about which is which.
Partner with legal and security to deploy solutions responsibly and maintain solid data governance.
Drive adoption, not just delivery: Getting something built is half the job—getting people to use it is the other half.
Document and systematize what you build so knowledge lives in the org, not in your head.
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.