Sr. Software Engineer (Platform Team)
$160,000–$225,000 year
On-site · Palo Alto, California, United States or Sunnyvale, California, United States
Job Summary
Sr. Software Engineer for SpaceX's AI platform leading design 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 frontier models, expansion of compute resources, and optimization of proxy systems for performance, security, logging, and control. Mentor engineers, build shared products/prompts/skills/infrastructure, and deliver solutions that enable rapid conversion of problems and ideas into tested software, deployed applications, and trained models on managed compute. Develop and scale tools that mitigate business risk, such as 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 ML researchers, security, and operations teams.
Required Qualifications
- 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)
- 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
Desired Qualifications
- Proven success building and scaling internal AI gateways, secure proxy systems, or MLOps platforms
- 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
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