Sr. Software Engineer (Platform Team)

Responsibilities

• Lead the design, architecture, and implementation of secure, scalable AI platforms and proxy systems used company-wide
• Own complex platform initiatives end-to-end, including technical strategy, implementation, testing, deployment, and long-term evolution
• Drive onboarding of new frontier models, expansion of compute resources, and optimization of proxy systems for performance, security, logging, and control
• Champion adoption across SpaceX by mentoring engineers, communicating value, building shared products/prompts/skills/infrastructure, and providing hands-on support
• Act as an entrepreneurial force to identify high-value opportunities and deliver solutions that allow users to rapidly convert problems and ideas into tested software, deployed applications, and trained models on managed, reliable compute
• Develop and scale tools that mitigate business risk, such as advanced AI-powered code review, PR automation, and safety guardrails
• Define best practices for lean, effective, and secure applied AI that maximizes conversion of engineering expertise into automation and reliable data systems
• Collaborate with and influence cross-functional stakeholders, including ML researchers, security, and operations teams

Requirements

• Bachelor’s degree in computer science, computer engineering, or other engineering discipline and 5+ years of professional experience building production software; OR 7+ years of professional experience building production software in lieu of a degree
• Experience developing and operating production platforms (AI/ML infrastructure, developer platforms, or large-scale backend systems)

Basic Qualifications

• Proven success building and scaling internal AI gateways, secure proxy systems, or MLOps platforms in a fast-paced environment
• Deep hands-on experience with Docker, Kubernetes, security architecture, and integrations across multiple cloud and frontier model providers
• Strong background in model onboarding, compute orchestration, observability, and infrastructure for high-volume AI usage
• Demonstrated ability to enable and mentor others through tools, documentation, training, and direct partnership
• Entrepreneurial track record of identifying opportunities and delivering outsized impact
• Proficiency in Python and strong experience with additional languages (Go, Java, TypeScript, Rust, etc.)
• Experience with infrastructure-as-code, CI/CD, and building highly reliable distributed systems
• Passion for AI risk mitigation, developer productivity, and turning complex engineering challenges into simple, scalable AI-powered outcomes