Opportunities in United States

Full Job Description

Partner with customers and engineering teams to define requirements for Azure Kubernetes Service capabilities supporting artificial intelligence workloads, and translate complex scenarios into coordinated engineering plans. Own and lead architecture for complex distributed-system components, evaluate trade-offs across security, reliability, scalability, performance, and cost, and align cross-team dependencies and design decisions. Lead by example through hands-on development of extensible, maintainable, well-tested, secure, and performant software, and improve the responsible use of artificial intelligence tools across the software development lifecycle. Define test strategies across components, mentor engineers in automated and security testing, and improve end-to-end validation to prevent regressions and raise solution quality. Lead automation of deployment and operational processes, establish safe rollout and rollback practices, and improve engineering tools and workflows across teams. Strengthen service observability and operational readiness, participate in on-call operations, lead investigation of complex production issues, and drive systemic improvements from incident learnings. Review complex designs and code, mentor engineers across teams, and advance shared engineering practices while upholding security, privacy, and compliance standards. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Go, or Java Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Go, or Java OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Go, or Java OR equivalent experience. 3+ years of experience developing or operating production Kubernetes-based services. 2+ years of experience leading delivery of a production cloud service or infrastructure feature across multiple engineering teams.