Forward Deployed Engineer

About SkyPilot

SkyPilot accelerates the world's most ambitious AI teams. SkyPilot turns fragmented AI compute across clusters into one optimized, highly available and easy-to-use pool: a single AI supercomputer.

SkyPilot (10k+ GitHub stars, 18M+ downloads) manages the GPU fleets of 100s of companies, from Fortune 500s to top AI-natives like Abridge, Applied Compute, Mistral, Unconventional AI, H Company, and Nubank, with usage growing exponentially. Born in the UC Berkeley lab behind Spark and Databricks, our growing team includes top-tier talent from Databricks, Google, Berkeley, MIT, CMU, and Cornell. To date, SkyPilot has raised over $20M in seed funding from top investors (incl. Lux, Coatue, Amplify) and operators (incl. Ali Ghodsi, Jeff Dean, Guillermo Rauch, Amjad Masad, Clem Delangue, Aaron Levie).

The role

SkyPilot powers frontier AI teams and enterprises that run our platform inside their own clouds, Kubernetes clusters, and data centers. We're looking for a Forward Deployed Engineer to embed with them end to end — deploying and integrating SkyPilot, shaping how their workflows map onto it (and how SkyPilot adapts to them), and solving the hard problems that stand between a customer and production. You'll own the technical side of making customers wildly successful. You're the person a frontier team leans on to get SkyPilot running in their own infrastructure.

What you'll do

• Partner with the teams building frontier AI: work hands-on with foundation labs and AI-natives to architect and deploy their production workloads on SkyPilot — across cloud, VPC, Kubernetes, and on-prem.
• Lead discovery and sales: design compelling sales demos, run the technical deep-dives that turn a customer's goals into a design they can ship, and build trust with the engineers and technical leaders — CTOs, VPs of Engineering, ML leads — driving the work.
• Fit SkyPilot to the customer — and the customer to SkyPilot: adapt their workflows to run well on SkyPilot, shape the product to how they work, and turn each engagement into a repeatable playbook.
• Bring the field back to the product: unblock the hard infrastructure problems in production, and carry customer signal back to the core engineering team.

What we're looking for

• You've deployed and integrated complex infrastructure or platform software into real customer environments, and you thrive in ambiguity.
• Strong systems and cloud fundamentals — comfortable across clouds, Kubernetes, and Linux, and able to debug someone else's environment.
• Strong Python (or similar) — enough to build the glue, tooling, and integrations a deployment needs.
• Genuinely customer-facing: you communicate clearly, build trust, and turn messy requirements into shipped solutions — you want to be where the product meets the real world.
• Experience as a forward-deployed or field engineer, familiarity with GPU / ML workloads and the tools to train and serve them, or a developer-facing / open-source background.

What we offer

• Competitive compensation and equity.
• Comprehensive medical, dental, vision coverage for you and your dependents.
• Company 401(k) plan.
• The chance to work with some of the best minds in cloud, distributed, and AI systems — with significant autonomy and ownership.
• A front-row seat at the latest open-source infra startup from Berkeley.
• Gourmet lunch & dinner for the team to do their best work.

Location: San Mateo, CA. Remote will be considered for exceptional candidates.