Job Summary
The Cortex team builds and operates the industry's leading SecOps platform, including XDR, XSIAM, XSOAR, and XPANSE. As a Senior Staff DevOps Engineer within the Cortex Production Engineering organization, you will play a key technical role in ensuring the reliability, scalability, availability, and operational efficiency of our large-scale cloud platform.
You will work hands-on with complex production systems while leading critical infrastructure, reliability, observability, and automation initiatives. You will partner closely with engineering teams to solve complex production challenges, improve platform architecture and operational readiness, and build automation that reduces operational toil.
This role requires strong technical depth, ownership, and the ability to lead complex initiatives across multiple engineering teams while mentoring other engineers and raising the technical bar across the organization.
Qualifications
•Design, build, and operate highly available and scalable cloud infrastructure supporting critical Cortex services.
•Lead complex DevOps, infrastructure, reliability, and automation initiatives from design through production implementation.
•Troubleshoot complex production issues across Kubernetes, cloud infrastructure, networking, storage, and distributed systems.
•Improve platform reliability through better monitoring, alerting, observability, capacity management, and operational practices.
•Build automation and self-healing capabilities that reduce manual operational work and improve incident response.
•Partner with application and platform engineering teams to improve production readiness, scalability, and service architecture.
•Participate in and provide technical leadership during high-severity production incidents, including root cause analysis and corrective actions.
•Design and improve Infrastructure as Code, CI/CD, and GitOps-based deployment and infrastructure management.
•Identify recurring operational problems and drive engineering solutions that permanently eliminate or reduce them.
•Mentor engineers, provide technical guidance, conduct design reviews, and help establish engineering best practices.
•Influence technical decisions across teams and drive adoption of scalable and reliable engineering solutions.
•Evaluate emerging technologies, including AI-assisted operations and automation, that can improve engineering productivity and operational efficiency.
Required Qualifications
•8+ years of experience in DevOps, Site Reliability Engineering, Production Engineering, Cloud Infrastructure, or related areas.
•Strong hands-on experience operating large-scale production environments.
•Deep knowledge of Kubernetes, containers, and cloud-native architectures.
•Strong experience with public cloud platforms, preferably Google Cloud Platform (GCP).
•Experience with Infrastructure as Code and automation technologies such as Terraform, Python, and GitOps.
•Strong understanding of CI/CD systems and modern software delivery practices.
•Experience with observability technologies such as Prometheus, Grafana, Thanos, OpenTelemetry, or similar platforms.
•Strong troubleshooting skills across Kubernetes, Linux, networking, cloud infrastructure, and distributed systems.
•Experience designing and operating highly available, scalable, and resilient production systems.
•Strong understanding of incident management, monitoring, alerting, SLIs/SLOs, and reliability engineering practices.
•Demonstrated ability to independently lead complex technical projects involving multiple engineering teams.
•Strong communication skills with the ability to explain technical decisions, influence stakeholders, and mentor engineers.
Preferred Qualifications
•Experience operating large-scale, multi-region SaaS or cloud platforms.
•Experience with GKE and other GCP services such as Compute Engine, Pub/Sub, BigQuery, and cloud networking.
•Experience designing or operating large-scale observability platforms.
•Strong programming or automation experience in Python, Go, or similar languages.
•Experience with automated remediation, self-healing infrastructure, or AI/AIOps technologies.
•Experience improving operational efficiency and reducing engineering toil through automation.
•Experience mentoring senior engineers and providing technical leadership across teams.
•Experience working with globally distributed engineering and operations teams.
Compensation
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 is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
$132,600.00 - $214,500.00/yr
Immigration Sponsorship
Is role eligible for Immigration Sponsorship? No. Palo Alto Networks will not sponsor applicants for work visas for this position.
