Principal Site Reliability Engineer

What you'll do

• Define and drive the long-term technical vision, architecture, and roadmap for reliability across the AI Platform Runtime.
• Architect highly available, resilient, secure, and scalable distributed platforms to power next-generation AI products.
• Design and develop AI agents and intelligent automation to accelerate platform operations, incident response, and troubleshooting.
• Establish platform-wide reliability standards including service-level objectives, error budgets, capacity models, and resilience patterns.
• Advance observability across complex distributed environments using OpenTelemetry, metrics, logs, traces, and automated anomaly detection.
• Lead cross-functional programs to identify systemic risks and improve availability, performance, security, and developer productivity.
• Provide technical leadership during critical incidents and translate post-mortem lessons into durable engineering improvements.
• Develop reference architectures and automation frameworks that can be adopted across multiple engineering organizations.

What we're looking for

• 15+ years of experience in Site Reliability Engineering, Platform Engineering, Distributed Systems, Cloud Architecture, or related roles.
• BS or MS degree in Computer Science or a related technical field involving significant software development, or equivalent experience.
• Demonstrated experience setting technical strategy and leading large-scale engineering initiatives across multiple teams or organizations.
• Deep expertise in distributed systems architecture, networking, Linux, Kubernetes, and public cloud platforms like AWS, Azure, or GCP.
• Strong proficiency in Python, Go, TypeScript, JavaScript, or Java for building production-grade automation and platform software.
• Extensive experience with infrastructure-as-code and platform automation tools such as Terraform, Crossplane, AWS CDK, or CloudFormation.
• Deep understanding of observability at scale including OpenTelemetry, metrics, logging, tracing, profiling, and analytics.
• Expertise in reliability engineering practices like SLOs, error budgets, capacity planning, fault tolerance, and incident management.
• Experience designing/operating AI/ML platforms, GPU infrastructure, or high-performance computing (preferred).
• Hands-on experience building AI agents or intelligent automation for infrastructure operations (preferred).
• Success establishing reliability architecture and engineering standards adopted across a large enterprise (preferred).
• Experience applying machine learning to capacity management, anomaly detection, or autonomous remediation (preferred).
• Recognized technical leadership through patents, publications, open-source contributions, or conference presentations (preferred).