Principal Software Engineer

In an unmarked building somewhere in Silicon Valley, a small team of engineers is working on what could become one of the most transformative technologies in enterprise computing: autonomous infrastructure that manages itself. Sailplane, backed by AI kingmaker Khosla Ventures (OpenAI's first investor) and seed specialist True Ventures, is building a "self-driving cloud" - intelligent agents capable of autonomously managing the largest and most advanced AI infrastructure on the planet.

Sailplane is solving one of the most complex challenges in modern computing: autonomous management of massive AI data centers. We are creating intelligent agents that operate rack-scale systems worth millions of dollars. Think Waymo for cloud infrastructure.

"We're building million-dollar agents," explains co-founder Sam Ramji, who previously led product at Google Cloud Platform and brought Linux to Microsoft. "These aren't consumer-grade chatbots - they're sophisticated autonomous systems managing rack-scale hardware worth millions per unit."

Sailplane is an early-stage AI infrastructure startup. Expect to wear many hats (writing code and evaluations, building infrastructure, working with customers). You will bring a startup mindset, eager to take ownership of projects, navigate ambiguity, and move quickly to solve challenging problems in a fast-paced environment.

As a Principal Engineer, you'll be a first-class generalist and leader moving across Sailplane agents and infrastructure. We need someone who thinks architecturally from first principles and can serve as the top technical IC and mentor for the team. You are a hands‑on technical leader who can turn AI research into a developer-friendly platform for infrastructure and platform teams. This is a senior technical individual contributor role focused on hands‑on coding, systems thinking, and prototyping.

You will act as a technical multiplier rather than a people manager.

This hybrid position reports to the CEO and is expected to work from our downtown San Francisco office 2 to 3 days per week.

• Design and evolve the control plane for agents: planning and execution loops, workflows, callbacks, and state models
• Implement sandboxing, dry‑run/preview modes, in variants, approvals, and rollback strategies so agents can safely change real infrastructure and applications
• Take hierarchical planning / agent research prototypes and build production‑grade agents, services and APIs around them (auth, rate limits, quotas, retries)
• Anticipate production system needs (security, networking, SLOs/SLAs) and instrument for reliability and usage via observability (logs, traces, guardrails)
• Guide architecture trade‑offs and reason about IP boundaries as an engineering design dimension
• Build, deploy, monitor, and operate LLMs in production on‑premises in diverse customer environments and implement MLOps best practices (CI/CD pipelines, containerization, continuous monitoring) to ensure reliable performance
• Lead through influence, setting engineering standards for code quality, testing, documentation, and on‑call practices
• Partner with founders to prioritize what to build next based on customer needs, market demand and technical implementation
• Conduct interviews and evaluate candidates across engineering, product, and design roles, helping build Sailplane's early team.

• ~10+ years of software engineering experience, including time operating at Staff/Principal scope or equivalent
• Deep experience in designing and building AI systems, large-scale distributed systems, infra/devtools, SaaS platforms, or other safety‑critical automation domains
• Strong proficiency in at least one backend language (e.g., Go, Rust, Java, C++), plus comfort with Python for glue/ML/agent work
• Hands‑on with cloud platforms (AWS/GCP/Azure), containers, CI/CD, and modern deployment practices (Kubernetes or equivalent)
• Track record of building systems and shipping with reliability and safety in mind
• Build a high‑trust, inclusive, feedback‑driven engineering culture that values autonomy, learning, and accountability
• Experience interviewing and evaluating…