Principal Site Reliability Engineer, Compute Infrastructure

At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values:
Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

The Team

Information Technology

As an AI-Native Reliability Software Engineer, you will build software engines, intelligent pipelines, and autonomous systems to power our cloud presence. You will design and optimize highly available cloud applications across AWS, and GCP, treating the cloud as a programmable, AI-orchestrated entity.

• Lead enterprise architectural strategy across AWS, Azure, and GCP, integrating AI workflows and LLM agents for automated infrastructure refactoring.
• Architect next-gen telemetry and secure-by-design pipelines, utilizing LLMs for dynamic IAM auditing and automated vulnerability patching at scale.
• Spearhead the engineering of autonomous agents using Go, Python, or Type Script to establish standards for predictive auto-scaling and self-healing systems.
• Act as the authority for complex anomalies, leading the design of internal AI agents for autonomous root-cause analysis and defect resolution.
• Define the technical vision for globally distributed Kubernetes fleets, championing AI-driven traffic routing and predictive capacity planning.

• 8+ years of experience in Cloud Software Engineering, SRE, or Distributed Systems Infrastructure (BS or equivalent).
• Strong track record with large-scale distributed systems, multi-cloud platforms (GCP, AWS), and container orchestration.
• Strong software engineering fundamentals in Type Script (Node.js), Go, or Python.

• At least 2+ years of hands-on experience integrating AI tools, LLMs, or predictive analytics into deployment workflows.
• Experience interfacing with LLM APIs, vector databases, and prompt engineering for systems-level orchestration.
• Experience designing agentic SRE workflows for autonomous incident response, automated root-cause analysis (RCA), and self-healing of distributed infrastructure.
• Experience building intelligent delivery pipelines using Git Hub Actions or Git Lab CI, featuring integrated automated testing, security gates, and AI-assisted code reviews.
• Ability to partner with Core AI/ML teams to bridge the gap between model deployment and high-availability cloud infrastructure.

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered…