Identify friction across lifecycle stages, including service introduction, ongoing operations, planned changes, breaking changes, deprecations, retirements, and post-event learning. Design and implement scalable workflows, tooling, and automation that make lifecycle requirements more consistent, measurable, and easier for service teams to complete. Use customer feedback, operational data, support signals, and service health indicators to prioritize improvements and define measurable outcomes. Improve the clarity, quality, and actionability of customer-facing lifecycle communications, including impact, required actions, timelines, dependencies, and support paths. Partner with engineering and business stakeholders to define standards, review readiness, resolve cross-team dependencies, and drive adoption of improved lifecycle practices. Build mechanisms that reveal customer and resource impact, track progress, identify risk, and enable timely intervention. Support customers during service lifecycle events Participate in a regular on-call rotation and respond to complex Azure service lifecycle events with significant customer or business impact. Assess impact, investigate technical signals, coordinate with product and live-site teams, and contribute to mitigation and recovery decisions. Translate fast-moving technical information into accurate, timely, and actionable updates for customers, support teams, stakeholders, and leadership. Escalate ambiguous or high-impact issues appropriately, maintain clear ownership, and help responders balance speed, customer needs, safety, and operational risk. Contribute to post-incident reviews, identify systemic gaps, and turn lessons learned into durable changes to telemetry, automation, documentation, processes, and service design. Provide expert service lifecycle response assistance and develop reusable guidance that improves response consistency across teams. Drive operational excellence and engineering quality Create and improve telemetry, health indicators, dashboards, and alerting that expose lifecycle and incident risk early and reduce avoidable noise. Independently implement reliable, scalable, secure, and high-performance solutions. Own design documentation, implementation plans, validation, rollback, and operational readiness. Automate repetitive analysis, validation, coordination, and reporting while preserving appropriate human review for consequential decisions and customer communications. Promote security, privacy, compliance, accessibility, resiliency, and reliability requirements throughout design and operations. Define and track measures for customer experience, timeliness, quality, adoption, risk reduction, and operational efficiency. Use root-cause and trend analysis to prevent recurrence and influence engineering teams to adopt improved standards and practices. Work effectively across service engineering, product engineering, support, field, communications, program management, business, data, security, privacy, and compliance disciplines. Proactively share information at the right level of technical depth for responders, service owners, customers, and executives. Resolve cross-team obstacles and conflicting priorities by clarifying customer impact, decision criteria, ownership, and next steps. Create and maintain troubleshooting guides, operating procedures, lifecycle playbooks, knowledge-base content, and reusable engineering patterns. Mentor and coach engineers, model sound operational judgment, and help others develop customer-focused solutions. Develop end-to-end expertise in Azure services, distributed systems, dependencies, failure modes, telemetry, and customer-impact pathways. Take ownership of service and workflow design with consideration for availability, reliability, resiliency, security, privacy, compliance, performance, scale, supportability, and cost. Use scripting, data analysis, APIs, automation, and AI-assisted engineering techniques to improve lifecycle execution and events response. Design solutions that support robust measurement of service health, customer impact, workflow quality, and lifecycle outcomes. Stay current as the cloud and AI technology landscape evolves, and apply relevant practices across related services and engineering teams. Bachelor's Degree in Computer Science, Information Technology, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Data Science, Cybersecurity, or related field AND 3+ years technical experience in software engineering, network engineering, service engineering, systems engineering, or industrial controls OR equivalent experience. Master's Degree in Computer Science, Information Technology, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Data Science, Cybersecurity, or related field AND 6+ years technical experience in software engineering, network engineering, service engineering, systems engineering, or industrial controls OR Bachelor's Degree in Computer Science, Information Technology, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Data Science, Cybersecurity, or related field AND 8+ years technical experience in software engineering, network engineering, service engineering, systems engineering, or industrial controls OR equivalent experience. 3+ years technical experience working with large-scale cloud or distributed systems. Experience supporting production services through an on-call rotation and responding to customer-impacting incidents. Experience improving service lifecycle, service health, change, deprecation, retirement, or operational-readiness processes. Experience with incident management, root-cause analysis, post-incident reviews, telemetry, monitoring, and reliability improvement. Experience designing or building automation, data-driven workflows, dashboards, or AI-assisted operational tools. Demonstrated ability to communicate complex technical issues clearly to customers, engineers, stakeholders, and leadership. Ability to influence across organizational boundaries and drive ambiguous, cross-functional work to measurable outcomes.