> Markdown version of [/jobs/ext/4011802-sr-staff-engineer-software](https://www.wearedevelopers.com/jobs/ext/4011802-sr-staff-engineer-software). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Staff Engineer Software - **Company:** Palo Alto Networks - **Location:** United States - **Experience:** Expert - **Salary:** $126,000.0 - $204,500.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Active Directory, Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, Profiling, Software Quality, Code Review, Databases, Continuous Delivery, Continuous Integration, Cursor, Programming Tools, Fault Tolerance, Iterative and Incremental Development, Internet Security, PostgreSQL, OAuth, Pair Programming, Redis, Openid Connect, Software Tools, Ansible, Security Assertion Markup Language (SAML), Software Engineering, .NET Core, GitHub Copilot, Autoscaling, Delivery Pipeline, Claude Code, SOAPAPI, Caching, Kubernetes, Information Technology, Terraform, Devsecops, AWS EKS, Docker, Microservices - **Published:** October 29, 2026 - **Apply:** https://www.careerbuilder.com/job-details/sr-staff-engineer-software--aedfb5ff-9f52-428c-be2f-6d872fe3830d ## About the Role Engineering Software, Leading Edge Technology, Internet Security, Artificial Intelligence (AI), Problem Solving Skills, Microservices, Business Growth, Technical/Engineering Design, Test Automation, Continuous Deployment/Delivery, * B.S. or higher in Computer Science or related technical field (or equivalent practical experience), with 5+ years of professional software engineering experience. * 2+ years of hands-on experience building, scaling, and operating large-scale microservices and distributed cloud-native applications (AWS, Azure, or GCP). * Solid experience building and operating microservices on containerized platforms (Docker, Kubernetes, AWS EKS, GKE, or AKS), including service meshes, autoscaling, observability, and production reliability patterns. * Demonstrated, hands-on proficiency with modern AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate design, implementation, and code reviews, with a clear judgment of when to leverage AI. * Technical Stack & Identity Domain: + Experience with .NET technologies (e.g., .NET / .NET Core and related frameworks). . + Expertise in REST/SOAP web services and knowledge of authentication/identity standards (SAML, WS-Fed, OpenID Connect, OAuth). + Experience with cloud infrastructure, automation, and deployment pipelines. * Strong knowledge of databases and caching technologies (PostgreSQL, Redis), data modeling, performance profiling, threat modeling, and secure-by-default design principles. * Excellent problem-solving skills and strong written/verbal communication skills to collaborate effectively and articulate technical trade-offs across cross-functional teams. Preferred qualifications: * Familiarity with Directory Services (e.g., Active Directory) is a plus. * Exposure to DevSecOps, compliance, and FinOps practices is a plus * Expertise in Infrastructure as Code with tools such as Terraform, Ansible is a plus ## Description * Architect, design, and implement highly scalable, distributed, and fault-tolerant microservices that support rapid growth and evolving business requirements. * Own the end-to-end execution of complex initiatives, delivering high-quality, maintainable, secure, and scalable solutions. * Partner closely with engineering, product, and infrastructure teams to evaluate feature requests and translate business needs into robust technical designs. * Drive continuous, iterative development using test-driven methodology, automated testing, and CI/CD practices to maximize code quality, supportability, and performance. * Diagnose and resolve complex production issues, partner with Support teams on customer escalations, and lead root-cause analyses. * Mentor and guide junior engineers through design discussions, pair programming, and code reviews to elevate technical capability across the team. * Leverage AI/ML to automate incident detection, root cause analysis, and remediation - reducing toil and accelerating mean time to resolution