Sr. Program Manager - Agentic AI for Azure Supportability

Microsoft•Redmond, WA

10h

About The Position

Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? Join Azure Engineering Operations (EngOps) – the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. As part of EngOps, you’ll design solutions that prevent issues before they happen, embed AI-powered automation, and turn signals into actions that deliver measurable customer impact. Our culture of empowerment, inclusion, and growth mindset defines how we work. Every day, customers stake their business and reputation on our cloud. You can help EngOps keep them secure, resilient, and ready. 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.

Requirements

Bachelor's Degree in Computer Science, Engineering, Data Science, Math, Business, or related field AND 4+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
4+ years of experience in engineering, product/technical program management, data analysis, or product development.
2+ years of experience in deep learning, ML, and/or AI
2+ years of working on technical B2B products and services.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

Hands-on experience in developing ML and/or AI based solutions.
Knowledge of deep learning optimization and acceleration techniques.
Firsthand experience with Azure, AWS, or Google Cloud.
Experience with data analytics and related technologies, including Kusto (Azure Data Explorer), SQL, ETL technologies, machine learning (ML), and Power BI.
Experience as a key contributor towards designing, shipping, and operating large-scale, cloud services or SaaS platforms.
Ability to write clear and concise business/technical/product requirement documents.
Ability to work well with and articulate ideas to people: customers, engineers, executives.
Proven combination of strong business acumen, deep technical knowledge, and excellent communication and storytelling skills that have allowed you to solve difficult problems and drive clarity for stakeholders in ambiguous settings.
Solid communication, presentation, and storytelling skills, with the ability to articulate complex technical and business concepts to diverse audiences.
Passion and experience in solving complex and ambiguous problems.

Responsibilities

Roadmap Development: Define and drive the agentic AI roadmap for Azure Supportability to meet customer experience and efficiency objectives.
Drive Clarity: Create, review, and gain alignment on BRD, PRD, and other documents to drive clarity with engineering and business teams.
Cross-Team Leadership: Partner with engineering, product, and support teams to align goals, OKRs, and delivery milestones for agentic AI initiatives.
Stakeholder Communication: Own all stakeholder management including clearly communicating benefits, providing routine updates, and creating feedback loops so that we can iterate effectively.
Derive Actionable Insights: Conduct research, interviews, and competitive analysis to stay ahead of the rapidly evolving AI landscape and identify customer needs, pain points, and opportunities.
Quantify Impact: Measure and evaluate the performance, adoption, and feedback for AI efforts, and continually iterate based on data and insights.
Technical Curiosity & Depth: Anticipate and deeply understand technical challenges, constraints and blockers faced and provide recommendations for solving these challenges in a methodical manner.

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