Top Tech Jobs & Startup Jobs in Boston, MA

Leads customer-facing cloud architecture engagements across Azure AI, applications, infrastructure, and data workloads. Advises executives, designs secure and scalable solutions, guides implementation and operational excellence, resolves technical blockers, oversees strategic account delivery, and accelerates Azure adoption. The role also includes mentoring peers, contributing technical thought leadership, supporting proposals, maintaining cloud certifications, and helping enterprise customers adopt AI and modernize applications at scale.

Lead Americas go-to-market strategy for Microsoft Power Platform (Power Apps, Power Automate, Power Pages). Design scalable GTM programs, enable field sales, build repeatable win formulas, drive seat/consumption growth, competitive positioning, cross-functional orchestration, and measurable revenue outcomes.

Develop and execute Cloud and AI sales enablement strategies for corporate, SMB, and partner teams. Build learning paths, technical skilling programs, seller communities, and field connection mechanisms. Identify capability gaps, analyze KPIs and customer feedback, measure business impact, and use insights to improve sales motions, revenue growth, consumption, adoption, and renewal. Collaborate across sales, engineering, marketing, partner, and technical success organizations to scale enablement programs.

Leads Azure capacity automation and backend tooling programs across Engineering, Finance, Operations, and capacity planning teams. Translates business needs into requirements, user stories, acceptance criteria, and workflow specifications; manages dependencies, risks, governance, and delivery. Improves processes through automation, data analysis, reporting, and AI-powered solutions such as Microsoft Copilot. Drives stakeholder alignment, change adoption, data quality, documentation, and operational excellence across capacity allocation and prioritization workflows.

Leads AI innovation and transformation across North America Consumer while owning Microsoft’s retail labor strategy and execution across major U.S. and Canadian partners. Responsibilities include developing AI pilots, driving adoption, managing outsourced labor agencies, optimizing deployment and coverage, setting KPIs, analyzing performance, managing budgets and contracts, and partnering across Sales, Marketing, Finance, Analytics, and retail teams to improve customer experiences and business impact.

Own Windows Consumer Retail strategy across North America, including category strategy, P&L, assortment, programs, investments, and performance management. Drive unit growth and market share against Mac and Chrome while coordinating Retail, OEM, Silicon, Sales, Marketing, Worldwide, and Finance stakeholders. Lead and develop a team of Senior Category Managers, manage hiring plans, and transform business operations through AI-enabled insights and execution.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Design and deliver distributed storage systems for AI and machine learning workloads at hyperscale. Lead architecture, development, testing, deployment, and innovations in scalability, performance, security, and efficiency. Collaborate with AI researchers and cloud infrastructure engineers, mentor engineers, and guide technical strategy for high-availability, durable, high-performance storage supporting training and inference.

Leads complex, cross-organizational technical programs connecting customer needs, AI innovation, cloud solutions, and business outcomes. Defines program vision, roadmaps, metrics, governance, and business cases; drives architecture, execution, risk management, and executive alignment. Partners with customers, engineering, product, security, and field teams, leads strategic engagements, improves operational processes, champions responsible AI and security, and mentors program managers.

Build and optimize inference systems and tools for generative AI models, collaborate with researchers to improve performance, profiling, debugging, and deploy large-scale distributed inference solutions.