Software Engineer (Platform Team)

SOFTWARE ENGINEER (PLATFORM TEAM) 

The Platform Team is responsible for building 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 products, prompts, skills, and infrastructure, this team unlocks reliable, high-impact AI capabilities across the entire organization. 

As a Software Engineer for SpaceX's AI platform, you will act as an entrepreneurial builder focused on the leanest and most effective applied use of AI at SpaceX. You will design platforms that convert engineering know-how into tested software, automation, and reliable data stores at scale while creating 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 work will directly accelerate SpaceX production and development by enabling every team to move faster with trustworthy AI. 

RESPONSIBILITIES: 

• Design, build, and operate secure, scalable AI platforms and proxy systems used by teams throughout SpaceX
• Own the full lifecycle of platform development including design, testing, deployment, and continuous improvement
• Drive adoption by communicating value, directly supporting engineers, and building shared prompts, skills, and infrastructure that accelerate peers
• Act entrepreneurially to identify high-value opportunities and create solutions that allow users to rapidly turn problems and ideas into tested software, deployed applications, and trained models on managed, reliable compute
• Collaborate closely with stakeholders to deeply understand needs and deliver platforms that connect AI to real tools and workflows
• Onboard new models, expand compute resources, and optimize efficiency of proxy systems for logging, control, and security
• Develop tools that mitigate business risk, such as AI-powered code review and PR automation
• Focus on lean, effective, and secure applied AI that maximizes conversion of engineering expertise into automation and reliable data systems across the company 

BASIC QUALIFICATIONS: 

• Bachelor’s degree in computer science, computer engineering, or other engineering discipline; OR 2+ years of professional experience building production software in lieu of a degree
• Experience developing production software systems (platform, backend, or full stack) 

PREFERRED SKILLS AND EXPERIENCE: 

• Experience building internal developer platforms, AI gateways, or secure proxy systems in production
• Hands-on work with Docker containers, security-focused architecture, and multi-provider integrations (cloud compute + frontier model providers)
• Familiarity with MLOps, model onboarding, compute orchestration, and infrastructure for large-scale AI usage
• Strong desire to enable others — experience creating tools, documentation, shared assets, or training that drives company-wide adoption
• Entrepreneurial mindset with a track record of identifying and delivering high-impact solutions
• Proficiency in Python and experience with additional languages (Go, Java, TypeScript, etc.)
• Knowledge of Kubernetes, container orchestration, observability, and infrastructure-as-code tools
• Understanding of AI risk mitigation, code generation, and developer productivity tools
• Passion for turning complex engineering problems into simple, reliable, and secure AI-powered outcomes