Job Description

As part of the Azure CXP CRE team, your responsibilities include: On-call Communication Management during regular on-call rotations *Join incident bridges and work with engineering to obtain real-time outage details. *Understand incident scope, impact, and mitigation to translate complex technical findings into clear, professional, and decisive updates for customers and stakeholders. *Keep communications consistent and fact-based throughout the incident; confirm information with engineering and leadership before sharing. *Assist with publishing Public Incident Reports and RCA summaries. *Support live site incident (LSI) operations, including triage, resolution, and post-incident analysis. *Shares details related to incidents and their resolution through post-mortem reports and during regular review meetings. Problem Management & Data Analytics *Design and implement automated detection systems to identify impacted resources in real time. *Collaborate with engineering and operations teams to enhance telemetry, monitoring, and alerting accuracy while reducing false positives. *Develop dashboards and visualizations in Power BI and Azure Data Explorer to support data-driven insights. *Build scalable data collection and analysis frameworks to improve service reliability and incident response. *Participate in incident resolution workflows and provide actionable insights to drive platform and process improvements. *Communicate technical findings and recommendations to stakeholders through clear, data-backed reporting. Tooling & Automation *Develop tools and analytics pipelines to automatically assess incident impact and blast radius across services, regions, and customers in real time. *Design and maintain automation solutions that enhance incident detection, monitoring, communication, and remediation while reducing operational toil and repeat issues. *Identify recurring problems, propose preventive solutions, and collaborate with engineers and teams to implement fixes. *Build and support no-code/low-code solutions to optimize operations and improve team efficiency. *Collaborate with product, infrastructure, and operations teams to align automation initiatives with organizational reliability and customer trust goals. Required Qualifications *Bachelor's degree in computer science, Information Technology, Data Science, Cybersecurity, or a related field AND 7+ years of technical experience in software engineering, network engineering, service engineering, systems engineering, or industrial controls; OR equivalent hands-on experience. *Hands-on experience implementing AI-driven solutions and automation, with proficiency in one or more programming/automation languages (e.g., C#, Java, JavaScript, Python) or equivalent expertise is a plus. *Certifications in cloud technologies (Azure, AWS, GCP), ITIL, or SRE frameworks are desirable. *Strategic thinking and a customer-first mindset; able to advocate for improvements in platform transparency and experience. *Excellent problem-solving, judgment, and decision-making skills, communication and collaboration skills. *Understanding of SRE principles, including SLAs/SLOs, telemetry, and monitoring. *Proven experience in cloud operations, incident & crisis management, or large-scale systems engineering ideally within platforms such as Azure, AWS, or GCP. *Contribute to a data-driven culture as well as a culture of experimentation across the organization. *Own and drive projects and features by working towards the team's defined goals and milestones. *Creating prototypes and proof-of-concepts for iterative development. *Be curious and willing to learn and grow. Preferred: 5+ Years of demonstrated experience as an Incident Commander or Crisis Manager for critical, high-severity incidents in high-availability, distributed environments. Experience with SRE (Site Reliability Engineering) principles and practices. Exposure to chaos engineering, fault injection, or high availability architecture. AI/ML Experience: [Beginner to Intermediate] Familiarity with how AI/ML models are integrated into cloud infrastructure and their potential failure modes. Experience using AI-powered tools for incident analysis, log correlation, or predictive alerting. An understanding of the challenges and risks associated with AI/ML systems in a production environment. Certifications: Relevant cloud certifications (e.g., AWS Certified DevOps Engineer, Azure Solutions Architect, GCP Professional Cloud Architect). Certifications in ITIL, SRE, or other relevant frameworks.

Skills Required