Principal Software Engineer (Platform Team)

PRINCIPAL SOFTWARE ENGINEER (PLATFORM TEAM)

The Platform Team builds the foundational tooling and security infrastructure that empowers every team at SpaceX to harness AI effectively. This team creates secure, scalable gateways and proxy systems that allow engineers and operators across the company to write code faster, perform advanced data analysis, connect AI to their daily tools and problems, and turn ideas into deployed solutions with confidence. By onboarding new frontier models, expanding compute capacity, optimizing proxy efficiency for logging and control, and building shared prompts, skills, and infrastructure, this team unlocks reliable, high-impact AI capabilities across the entire organization.

As a Principal Software Engineer for SpaceX's AI platform, you will set the technical vision and serve as a senior leader and entrepreneurial force for the leanest and most effective applied use of AI at SpaceX. You will architect platforms that convert engineering know-how into tested software, automation, and reliable data stores at massive scale while pioneering risk-mitigation tools such as intelligent code review and PR assistants. Current systems are built with Docker containers acting as secure gateways and proxies that integrate with any cloud compute provider and multiple frontier model providers. Your strategic leadership will be critical to accelerating SpaceX production and development by making trustworthy AI a core capability for every team at SpaceX.

RESPONSIBILITIES:

• Define and drive the long-term technical vision and architecture for SpaceX’s AI platform and security infrastructure
• Lead high-impact initiatives with full ownership over strategy, design, implementation, and successful company-wide rollout
• Oversee onboarding of frontier models, massive compute scaling, and continuous optimization of proxy systems for security, efficiency, logging, and control
• Lead adoption efforts at scale — establishing standards, mentoring senior engineers, building reusable assets, and driving cultural change toward AI-first workflows
• Proactively identify and execute on the highest-leverage opportunities to turn ideas into production software, trained models, and automated systems with managed, reliable compute
• Invent and scale advanced risk-mitigation capabilities (AI code review, automated PR tools, safety systems) that protect and accelerate the business
• Establish best practices and technical direction for lean, secure, and maximally effective applied AI across the company
• Serve as a key technical advisor and collaborator with leadership and cross-functional teams to align platform capabilities with SpaceX’s most ambitious goals

BASIC QUALIFICATIONS:

• Bachelor’s degree in computer science, computer engineering, or other engineering discipline and 7+ years of professional experience building and scaling production platforms; OR 9+ years of professional experience building and scaling production platforms in lieu of a degree
• Experience designing and operating large-scale AI/ML platforms, internal developer platforms, or mission-critical infrastructure

PREFERRED SKILLS AND EXPERIENCE:

• Demonstrated success architecting and scaling AI gateways, secure proxy layers, or enterprise MLOps platforms that serve hundreds of users
• Expert-level experience with Docker/Kubernetes ecosystems, zero-trust security models, and multi-cloud/frontier-model integrations
• Deep expertise in MLOps, distributed compute, model lifecycle management, and building highly observable, reliable systems
• Strong history of enabling organization-wide impact through technical leadership, mentoring, and creation of shared platforms and standards
• Entrepreneurial leadership with a proven ability to spot and deliver transformative solutions
• Mastery of Python and broad expertise across modern languages and tooling
• Extensive experience with infrastructure-as-code, advanced observability, and building platforms that others love to use
• Deep passion for responsible AI, developer velocity, and converting deep engineering knowledge into reliable automation at planetary scale