Principal Site Reliability Engineer, Compute Infrastructure

What you'll do

• Lead enterprise architectural strategy across AWS, Azure, and GCP while integrating AI workflows and LLM agents.
• Architect secure-by-design telemetry pipelines using LLMs for dynamic IAM auditing and automated vulnerability patching.
• Engineer autonomous agents in Go, Python, or TypeScript to create predictive auto-scaling and self-healing systems.
• Design internal AI agents to perform autonomous root-cause analysis and resolve complex system anomalies.
• Define the technical vision for globally distributed Kubernetes fleets with AI-driven traffic routing and capacity planning.
• Build intelligent delivery pipelines featuring automated testing, security gates, and AI-assisted code reviews.
• Partner with Core AI/ML teams to bridge the gap between model deployment and high-availability cloud infrastructure.

What we're looking for

• 8+ years of experience in Cloud Software Engineering, SRE, or Distributed Systems Infrastructure (BS or equivalent).
• Proven track record with large-scale distributed systems, multi-cloud platforms (GCP, AWS), and container orchestration.
• Strong software engineering fundamentals in TypeScript (Node.js), Go, or Python.
• At least 2+ years of hands-on experience integrating AI tools, LLMs, or predictive analytics into deployment workflows (preferred).
• Experience interfacing with LLM APIs, vector databases, and prompt engineering for systems-level orchestration (preferred).
• Experience designing agentic SRE workflows for autonomous incident response, root-cause analysis, and self-healing of distributed infrastructure (preferred).
• Experience building intelligent delivery pipelines using GitHub Actions or GitLab CI with automated testing and security gates (preferred).
• Ability to partner with Core AI/ML teams to bridge the gap between model deployment and high-availability cloud infrastructure (preferred).