Jobs at Microsoft

Design, implement, test, deploy, and operate highly available distributed services for Azure Monitor at global scale. Build telemetry collection, routing, storage, and data-access APIs and tools; improve reliability, security, observability, and diagnostics; and integrate machine learning and AI-assisted operational capabilities. Participate in on-call and incident response, collaborate across teams, mentor engineers, lead design reviews, and drive architectural alignment.

Design, implement, and operate scalable, reliable components of distributed messaging and control-plane infrastructure for Azure Messaging. Write production-ready code, optimize performance, perform code reviews, apply testing and reliability practices, and collaborate across teams to support deployment and live-site operations.

Designs, builds, and operates scalable AI-powered production systems for Microsoft 365 Copilot. Responsibilities include architecture ownership, secure and tested coding, AI-native software delivery, deployment automation, observability, incident response, reliability, compliance, and collaboration with engineers and applied scientists on large language model and agentic experiences.

Own the vision, strategy, roadmap, delivery, reliability, adoption, and competitive positioning for Microsoft Fabric Eventstream’s Kafka endpoint. Lead customer discovery through growth, prioritize platform and user experience investments, and partner with engineering, design, data science, security, customers, and partners. Drive technical storytelling, field readiness, go-to-market planning, and AI-assisted experiences for real-time data and streaming applications.

Lead AI and security technology strategy for government customers, translating business priorities into Microsoft solution roadmaps. Build trusted relationships with technology executives, design AI transformation plans, develop initial agentic solutions, and orchestrate Microsoft and partner teams. Lead technical governance, consultative customer engagements, secure AI adoption, and commercial growth while applying industry knowledge to address customer opportunities, threats, and barriers.

Owns end-to-end product design for Microsoft Fabric real-time intelligence experiences. Responsibilities include user research, interaction and UX design, human-AI collaboration patterns, rapid prototyping, validation, design systems, and cross-functional partnership with engineering, product, research, and data teams.

Lead and develop a high-performing engineering team building scalable Azure data integration cloud services. Set technical strategy, guide architecture and engineering investments, improve reliability and operational excellence, oversee deployment automation, and support production services and incident response. Partner with product leaders and stakeholders to align execution with customer needs, while driving hiring, talent development, inclusion, and continuous learning.

Designs and builds runtime infrastructure, deployment, upgrade, and orchestration systems for globally distributed Azure Managed Redis clusters. Responsibilities include integrating Redis Enterprise with Azure, improving scalability, reliability, security, observability, testing, and operational excellence, while writing production-grade C# and Go code. The role also develops AI-assisted engineering workflows, collaborates across teams, and mentors engineers in distributed systems and cloud-native architecture.

Manages multiple medium-enterprise accounts, develops strategic account plans, builds C-level and technical relationships, and drives Microsoft solution sales and digital transformation. Coordinates internal teams and partners, manages pipelines and forecasts, identifies upsell and cross-sell opportunities, positions business and technology solutions, and serves as a trusted customer advisor. The role requires consultative selling, executive engagement, industry awareness, customer success oversight, and achievement of revenue and consumption targets.

Lead and grow a solution engineering team for AI-powered Dynamics 365 business solutions. Own technical win strategy, coach demos and solution design, partner with sales to convert pipeline, enable value assessments, manage proposals, and align with partners and Customer Success to achieve revenue and deployment outcomes.

Leads the design, development, testing, debugging, and operation of scalable distributed systems for Fabric data mirroring. Responsibilities include architecture, coding, code reviews, dependency management, telemetry and root-cause analysis, automated testing, reliability, security, performance optimization, and collaboration with technical and project stakeholders.

Design, develop, test, and maintain scalable distributed software and data movement services for Microsoft Fabric. Investigate issues using debugging, telemetry, logs, and monitoring; participate in root cause analysis, code reviews, design documentation, automated testing, and CI/CD. Collaborate with engineers, architects, product managers, designers, and partners to deliver secure, reliable, performant features and improve customer experiences.

Build and prototype polished, high-fidelity customer-facing web components and UX platforms; iterate based on user and stakeholder feedback; use data to drive improvements; create wireframes and experiments; integrate with backend services via REST/GraphQL and ensure designs scale.

Design, build, and operate high-scale data movement and replication services for Microsoft Fabric. Lead architecture, code quality, debugging, testing, and cross-team dependency planning. Mentor peers, drive reliability, performance, and observability, and ensure security and compliance for distributed systems.

Establishes and operates an ongoing AI optimization framework for strategic customer engagements. The role improves workflows, adoption, prompts, enablement materials, and agent performance using Copilot, usage data, and behavioral signals. Responsibilities include detecting agent drift, prioritizing high-ROI investments, facilitating kaizen improvement cycles, embedding standard work and ownership, and transferring the capability to customer teams. The position also leads multidisciplinary teams and manages multiple projects or portfolios.

Leads enterprise AI workforce transformation by redesigning operating models, business processes, employee roles, and human-agent collaboration. Designs and deploys AI agents, develops AI literacy and retraining programs, embeds adoption into performance and onboarding systems, and protects employee privacy. Directs readiness assessments, change programs, AI councils, champion networks, global training, stakeholder workshops, and adoption analytics to ensure sustained behavioral change across large organizations.