Cloud Engineer II (Full Time) - United States at Cisco in San Francisco, CA

  • Company: Cisco
  • Location: Usa-san Francisco
  • Salary: $112K – $203K
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-09-14

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Job description

Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Meet the Team Our Security Policy and Access team is at the heart of Cisco’s mission, building and operating market-leading platforms like the Cisco Identity Services Engine and Meraki Access Manager to simplify security compliance for global organizations. We are a critical engine within our $3B+ Security Business Group, directly enabling Cisco’s strategic pivot to a software-first, recurring revenue model that secures the world’s most vital networks. You will join a high-performing, collaborative group of engineers, architects, and product experts who thrive in an Agile environment where cross-functional teamwork is the daily standard. What makes us truly exciting is the scale of our impact; we are building cloud-native, AI-integrated solutions that solve the most complex challenges in zero-trust security and identity management. If you are passionate about owning services from design to production and want to work on a team that values innovation, reliability, and continuous learning, this is the place to make your mark. Your Impact The team is made up of builders and problem-solvers who enjoy tackling complex distributed systems challenges while supporting highly scalable, resilient, and observable services in production. What makes this team especially exciting is the opportunity to work at the intersection of cloud engineering, cybersecurity, automation, networking, and AI-assisted development while directly influencing products used by some of the world’s largest organizations. Design, Develop, test, deploy, and support cloud-native SaaS applications and services. Build scalable, resilient, and secure distributed systems using microservices architecture. Develop and operate services running in public cloud environments such as AWS, Azure, or Google Cloud. Participate in the design and implementation of service automation, monitoring, observability, and telemetry pipelines. Analyze service health, performance metrics, logs, traces, and alerts to improve reliability and customer experience. Work on deployment, configuration, and operational readiness for SaaS services in production environments. Review designs, implementation and test plans, and operational procedures. Troubleshoot complex production and customer issues across application, infrastructure, database, and networking layers. Collaborate with engineering, product management, security, SRE, DevOps, and customer-facing teams. Contribute to building secure, scalable, and reliable business solutions for Cisco customers and partners. Minimum Qualifications Meet one of the following (completed within the past 3 years or expected to be completed within the next 12 months): A Master's degree with 0 years of work experience; or A Bachelor's degree with 2 years of work experience. Qualifying education and work experience should be in Computer Science, Software Engineering or a related field. 2+ years of software engineering experience in a SaaS product company; and hands-on experience developing or operating SaaS applications in a public cloud environment such as AWS, Azure, or Google Cloud will be added advantage. Programming experience in one or more languages such as Java, Python, or Go and experience designing and implementing REST APIs and backend services. 2+ years of hands-on experience deploying and operating microservices on Kubernetes / AWS EKS in production Preferred Qualifications Knowledge on networking fundamentals such as TCP/IP, HTTP, DNS, load balancing, and network security concepts. Experience debugging and problem-solving skills across application, infrastructure, and cloud service layers. Experience with Generative AI, including large language models, prompt engineering, AI-assisted development workflows, and respons

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