Principal Site Reliability Engineer (AI Platform Architecture)

Key Responsibilities:

• Defining the reliability architecture for AI compute services, including SLO frameworks, fault tolerance patterns, and advanced capacity planning models.

• Driving hands-on development of automation and tooling that scales the SRE team's impact and eliminates operational toil.

• Designing a comprehensive observability strategy, leveraging existing platforms to build specialized telemetry and GPU-specific monitoring for AI workloads.

• Architecting deployment safety standards, including progressive rollouts, canary analysis, and automated rollback processes.

• Embedding reliability into the development lifecycle by influencing product engineering architecture and high-level design decisions.

• Mentoring and elevating the SRE team through design reviews, code reviews, and hands-on problem-solving.

Requirements:

• Extensive experience in SRE or platform engineering, with a proven track record of impact at a principal or staff level.

• Deep expertise in Kubernetes, specifically in managing autoscaling, resource scheduling, and orchestration for compute-intensive workloads.

• Advanced programming expertise in Python or Go, with experience building production-grade automation and platform services.

• Proven ability to influence cross-team technical decisions and elevate technical standards across engineering departments.

• Experience or strong technical interest in AI/ML infrastructure, model deployment, and GPU workload optimization.

• A system-level approach to designing reliability into innovative platforms while building strong partnerships with product engineering teams.