Job description

Our Mission 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. Who We Are 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. Job Summary The Team Information Technology Job Summary 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. Key Responsibilities 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 TypeScript 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. Qualifications Required Qualifications 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 TypeScript (Node.js), Go, or Python. Preferred Qualifications 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 GitHub Actions or GitLab 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. Compensation Disclosure 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 compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here . $175,400.00 - $283,800.00/yr Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations paloaltonetworks.com . Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Requirements

Must-haves

Information Technology
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 TypeScript 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 TypeScript (Node.js), Go, or Python.
At least 2 years of hands-on experience integrating AI tools, LLMs, or predictive analytics into deployment workflows.

Nice-to-haves

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 GitHub Actions or GitLab 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.
Compensation Disclosure
$175,400.00 - $283,800.00/yr
Our Commitment
We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsgcpazurellmgopythontypescriptkubernetesnode.jsml

Platform: workday
Effort: long

Benefits

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Vision