GTM Engineer
US$175,000 – US$200,000 / yr base salary
Posted 25 Aug 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$175,000 – US$200,000 / yr |
|---|
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
Baseten's GTM org is in hyper growth. As it grows and matures, the needs of the GTM stack get more sophisticated with scale — and this team exists to stay ahead of those needs. Our GTM Engineering team plays a critical role in building and maintaining the connective tissue across Baseten’s GTM tools, processes, and user experience for the field.
The GTM tooling landscape is changing fast, and the teams that win are the ones that adapt and iterate the fastest. This role exists to make sure Baseten is one of them.
You'll design, build, and ship AI-powered workflows that scale our GTM functions as a competitive advantage. We want someone who can walk in, audit what we have, identify what we're missing, and start shipping fast.
You know when to reach for Clay and when to build something custom in Claude Code. You think two to three steps ahead about how the thing you build today fits into the broader systems architecture tomorrow. And you bring a point of view — on our stack, on what we should be building, and on where AI can do something low-code tooling simply can't.
RESPONSIBILITIES
-
Ship AI-powered workflows for the field — build the agents and automations that give reps and managers real leverage, off-loading the manual and repetitive work. Reach for AI where it does something low-code can't.
-
Get insights in front of reps — turn Salesforce, warehouse, and usage data into the dashboards, scores, and alerts reps actually act on. A build isn't done until the field is using it.
-
Audit the stack and generate your own backlog — we have a lot of tools, some overlap, and real gaps. Walk in with a point of view, identify what's missing or broken, and prioritize without waiting to be handed a roadmap.
-
Ship rep-productivity workflows fast — triage asks from the field, find the low-hanging fruit, and build it. A good week looks like a VP of Sales asking for something Monday and having it live by Wednesday.