Overview
Are you a customer-obsessed, AI-driven program leader who thrives at the intersection of engineering, operations, and applied AI? The Azure Engineering Operations EngOps team is on a mission to transform Microsoft Cloud customers into lifelong advocates by delivering intelligent, scalable, and frictionless support experiences.
Within EngOps, the ACES organization is leading the shift to AI-first support delivery—leveraging agentic AI, LLM-powered systems, and real-time operational intelligence to reduce customer friction, improve reliability, and drive down support volume at Azure scale.
We are seeking a Senior Customer Engineering Program Manager – AI Operations to define and operationalize the next generation of AI-powered support systems for Azure Engineering Direct AED. In this role, you will combine program leadership, data-driven decision making, and applied AI strategy to build intelligent support experiences that proactively resolve issues, empower engineers, and transform customer outcomes.In this role, you will transition AED from reactive support to predictive, AI-driven operations by scaling agentic AI systems that autonomously diagnose, recommend, and resolve issues. This transformation will drive measurable improvements in case volume reduction, MTTR, and customer satisfaction, while establishing AI Ops as a core pillar of support delivery excellence.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
• Define and execute the AI Operations strategy for AED, aligning to business goals such as case deflection, resolution time reduction, and support scalability
• Translate customer pain points and operational gaps into AI-powered solutions including agent workflows, copilots, and automation systems
• Partner with engineering teams to bring agentic AI services LLMs, RAG, multi-agent orchestration from concept to production
• Drive adoption of AI agents and copilots across ACE workflows triage, diagnostics, mitigation, knowledge retrieval
• Define requirements for multi-agent systems, tool integrations, and workflow orchestration to enable autonomous issue resolution
• Ensure solutions are grounded in real-time Azure signals, telemetry, and knowledge systems
• Own the end-to-end lifecycle of AI-powered operational capabilities: design, experimentation, deployment, monitoring, and continuous improvement
• Establish evaluation frameworks success metrics, golden datasets, feedback loops to measure AI effectiveness, quality, and safety
• Embed Responsible AI practices ensuring systems are safe, compliant, and al
