Senior Staff Software Engineer (Performance Engineering)

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 Job Summary As a Performance Engineer for our Identity Security Product, you will design and execute a comprehensive performance engineering strategy. This role requires a hands-on engineer who not only identifies performance degradation but actively investigates, debugs, and implements code-level and database-level fixes. You will work to ensure our SaaS-based IAM systems are ultra-fast and scalable, while championing AI to transform performance data into actionable optimization strategies. Key

Responsibilities Identify, investigate, debug, and fix performance bottlenecks, memory leaks, CPU spikes, and thread contentions. Optimize SaaS application performance using deep knowledge of the .NET ecosystem. Analyze complex queries, optimize execution plans, and tune databases to eliminate deadlocks and contention. Apply a strong understanding of AI, LLMs, and prompt engineering to build diagnostic and automation frameworks. Dissect complex distributed system issues and formulate clear, actionable execution items for the development team. Utilize AI tools to analyze trace context, error logs, and system states for predictive recommendations and code remedies. Apply system design principles and patterns to build scalable performance frameworks and recommend architectural optimizations. Model and simulate realistic, high-concurrency identity workloads (OAuth2/OIDC, SAML, MFA). Implement 'Performance-as-Code' test suites using K6 or Gatling and integrate them into CI/CD pipelines. Collaborate with SRE to integrate chaos engineering to validate system resiliency. Utilize Generative AI to create synthetic test data and user behavior models from production logs. Harness AI-powered APM engines for autonomous bottleneck detection to reduce Root Cause Analysis (RCA) cycle time. Set up and maintain full-stack telemetry dashboards using tools like DataDog, Grafana, or OpenTelemetry.