Take ownership of important areas of the Azure SRE Agent Platform, including agent capabilities, orchestration, evaluation, user experiences on different form factors and supporting platform services Build and iterate on agentic systems, including tools, planning and execution loops, evaluations, and safety mechanisms Design and ship reliable capabilities that improve incident detection, diagnosis, mitigation, and operational learning Use telemetry, experiments, evaluations, and user feedback to guide iteration and investment Contribute to resilient, observable systems that operate safely and effectively in production Partner closely with engineers, SREs, and product counterparts to turn ambiguous problems into high-quality shipped solutions Participate in debugging, live-site learning, and post-incident hardening to continuously improve system quality Contribute to architecture, engineering standards, and development practices across the team Bachelor's or Master's degree in Computer Science, or equivalent practical experience. 7+ years of experience building production software using one or more modern programming languages such as C#, C++, Go, Java or Python. Strong understanding of Generative AI & software engineering fundamentals, data structures, and problem-solving. Ability to learn new technologies quickly and adapt to deliver customer and business impact. These requirements include but are not limited to the following specialized security screenings: Hands-on experience of building and operating LLM powered agentic systems in production, with direct ownership over quality, reliability, and iterations 4+ years of experience building and operating cloud platforms or distributed services, with depth in service architecture, deployment, and observability Strong product mindset with a track record of owning ambiguous problem spaces and driving them to high-quality outcomes Solid engineering fundamentals, including systems design, performance, and debugging in complex production environments Track record of designing, running, and optimizing evaluations for agentic systems, including tools, prompts, and agent loops Expertise with Kubernetes, container orchestration, or cloud-native infrastructure is a strong plus Experience contributing to or leading open-source projects at scale is a plus
