Staff Software Engineer – Performance & Reliability (Cloud Platform) - hybr at CyberArk

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

29 Jul, 26

Salary

225000.0

Posted On

30 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Go, Java, Python, Performance engineering, Distributed systems, Cloud-native architectures, Observability, Prometheus, Grafana, Datadog, CI/CD, Linux, Networking, Kubernetes, Infrastructure as code, System-level thinking

Industry

Computer and Network Security

Description

Company Description About CyberArk CyberArk, a Palo Alto Networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. CyberArk’s AI-powered Identity Security Platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. With Identity Security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, IT, developers and machines, to securely access any resource, located anywhere, from everywhere. Learn more at cyberark.com. Copyright © 2026 CyberArk Software. All Rights Reserved. All other brand names, product names, or trademarks belong to their respective holders. Job Description CyberArk is building the cloud platform that secures machine identities at scale. We’re looking for a Staff Software Engineer to lead performance and reliability engineering across distributed, microservices-based systems. In this role, you will define how system behavior is measured, tested, and improved under real-world load — building the frameworks, tooling, and standards that enable teams to deliver scalable, production-ready services. You will operate at the intersection of quality, production engineering, and distributed systems, driving performance engineering as a core capability across the platform. What You’ll Do Define and drive performance and reliability engineering strategy across cloud-native, distributed systems Design and build frameworks, tooling, and infrastructure for performance testing and system analysis at scale Establish performance baselines, SLIs/SLOs, and measurable standards across services Partner with engineering teams to embed performance testing into CI/CD workflows and development lifecycles Analyze system behavior under load and identify bottlenecks across application, infrastructure, and data layers Use observability data to interpret latency distributions, throughput, and failure patterns, and translate findings into actionable improvements Build reusable performance tooling and test platforms adopted across multiple teams Influence system design by advocating for scalability, resilience, and production readiness early in development Drive adoption of performance and reliability practices across teams, acting as a technical leader and subject matter expert Mentor engineers and contribute to raising the bar for system-level thinking and engineering quality #LI-KR1 #LI-Hybrid Qualifications 8+ years of experience in software engineering, SDET, performance engineering, or backend engineering roles Strong coding skills in Go, Java, or Python, with experience building frameworks or system-level tooling Proven experience designing and building performance testing systems, platforms, or frameworks Deep understanding of: performance testing methodologies (load, stress, soak, spike) workload modeling and traffic patterns latency (p50/p90/p99), throughput, and system behavior under load Experience working with distributed systems and cloud-native architectures Strong experience with observability platforms (Prometheus, Grafana, Datadog, etc.) Experience integrating performance testing into CI/CD pipelines at scale Solid understanding of Linux systems and networking fundamentals (TCP/IP, DNS, HTTP/S) Experience driving technical direction or influencing engineering practices across multiple teams Nice to Have Experience building or extending custom load testing frameworks (k6, Locust, Gatling, etc.) Experience with containerized environments and orchestration (Kubernetes) Familiarity with cloud infrastructure behavior under load (autoscaling, load balancing, storage systems) Experience in SaaS or security-sensitive systems Exposure to PKI, certificate lifecycle management, or identity systems Experience with Infrastructure as Code (Terraform, Ansible) What Sets You Apart Ability to operate across teams and influence engineering direction Strong system-level thinking across application, infrastructure, and data layers Proven ability to drive adoption of technical practices at scale Ability to translate performance insights into engineering decisions and product impact Clear communication of complex system behavior to both technical and non-technical stakeholders Why This Role Define and scale performance engineering across a high-impact cloud platform Work on distributed systems operating at enterprise scale Influence architecture and engineering practices across multiple teams Partner with experienced engineers solving complex system challenges Additional Information CyberArk is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status. The salary range for this position is $181,000 – $225,000/year, plus bonus, which will be based on the employee’s performance and equity. Base pay may also vary considerably depending on job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits.

Responsibilities

Define and drive performance and reliability engineering strategy across distributed, cloud-native systems. Build frameworks, tooling, and standards to measure and improve system behavior under real-world load.