Embed with customers to deploy and integrate SkyPilot across cloud, VPCs, Kubernetes, and on-prem; lead technical discovery and sales, design production workflows, debug customer infrastructure, and feed product signals back to engineering to create repeatable playbooks.
About SkyPilot
The role
What you'll do
What we're looking for
What we offer
SkyPilot accelerates the world's most ambitious AI teams. Every hour they spend fighting infrastructure is an hour the frontier doesn't move — so SkyPilot turns fragmented compute across clusters into one optimized, highly available and easy-to-use pool: a single "AI supercomputer."
SkyPilot (10k+ GitHub stars, 14M+ downloads) is deployed at 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.
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.
- 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.
- Competitive compensation and equity
- Comprehensive medical, dental, vision coverage for you and your dependents
- 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 (lineage: Databricks, Anyscale).
- Gourmet lunch & dinner for the team to do their best work
Location: San Mateo, CA. Remote will be considered for exceptional candidates.
Similar Jobs
Artificial Intelligence • Machine Learning
Lead end-to-end design and delivery of enterprise-scale Agentic AI solutions across multiple customers and industries. Architect robust, scalable, secure systems (RAG, multi-agent, SLM/LLM, multimodal), mentor Forward Deployed Engineering teams, partner with senior customer stakeholders, define best practices and reusable frameworks, drive post-delivery optimization, and publish thought leadership while ensuring governance, observability, and compliance.
Top Skills:
Emotion AiFine-TuningGenerative AiGoGpu InfrastructureJavaJavaScriptKnowledge AiLangchainLanggraphLlmMulti-Agent OrchestrationOpenaiPrompt EngineeringPythonRagRetrieval OptimizationsSlmSQLVector DatabasesWorkflow Automation
Artificial Intelligence • Software
Deploy, operate, and maintain Palantir infrastructure for government customers. Responsibilities include monitoring, alerting, configuration management, upgrades, migrations, production troubleshooting, automation of operations and runbooks, on-call support, and developing infrastructure solutions using Palantir Foundry and Apollo.
Top Skills:
AIBashGoJavaJavaScriptLlmPalantir ApolloPalantir FoundryPython
Cloud • Information Technology • Security • Software • Cybersecurity
Embed with a strategic customer to design, build, and deploy production-ready code on the Cloudflare platform. Own technical strategy, operational reliability, platform adoption, and incident response while surfacing product feedback and partnering with senior customer and Cloudflare engineering leadership. Maintain regular on-site presence.
Top Skills:
AWSAzureCloudflare Developer PlatformCloudflare WorkersGCPOpencodeServerlessWindsurf
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



