Jobs at Microsoft

Develop and execute Microsoft Advertising sales strategies, grow client revenue, manage pipelines, expand product adoption, and build strategic relationships with C-level and senior marketing stakeholders. Lead account planning, negotiations, opportunity management, and cross-functional collaboration to achieve sales targets and improve customer satisfaction.

Develops Microsoft Advertising agency partnerships across North America by creating growth plans, identifying advertiser opportunities, driving product adoption, and coordinating sales, marketing, product, technical, and learning teams. Leads agency enablement programs, workshops, commercial initiatives, pipeline management, performance analysis, and scalable growth motions across advertiser portfolios. Requires strong digital advertising, strategic selling, cross-functional collaboration, and business planning expertise.

Leads the commercial development of Microsoft for Startups portfolios across manufacturing, energy, cybersecurity, and AI. Develops industry investment theses, identifies high-potential startups, drives enterprise customer access, manages co-sell and marketplace execution, coaches founders on go-to-market strategy, transitions startups into managed sales coverage, and builds relationships across venture capital, partner, customer, and industry ecosystems.

Leads executive searches for Partner, Vice President, and Corporate Vice President roles, especially in engineering and technical domains. Advises senior leaders on talent strategy, succession planning, organizational design, and workforce planning. Builds executive pipelines, assesses leadership talent, manages candidate experience and closing strategies, and uses market intelligence, AI-enabled tools, and talent analytics to improve hiring outcomes.

Lead the training, optimization, scaling, and debugging of large language and multimodal generative models for scientific discovery. Develop efficient training workflows, identify performance bottlenecks, guide technical strategy, mentor engineers, and collaborate with researchers and domain experts to translate advanced machine learning research into impactful solutions.

Lead Microsoft Foundry’s enterprise security and governance strategy and roadmap for AI models, agents, and platform capabilities. Partner with engineering, security, compliance, identity, governance, and field teams to deliver secure AI capabilities for enterprise, regulated, and government cloud environments. Translate customer needs and telemetry into scalable product improvements, engage CISOs and industry analysts, and drive cross-functional execution, adoption, and product growth.

Conduct machine learning and statistics research alongside Microsoft researchers, applied scientists, and engineers. Interns will develop or contribute to theoretical and applied research, collaborate with peers and mentors, present findings, and support research and development projects across areas such as generative models, causal inference, reinforcement learning, deep learning, and forecasting.

Leads consultative Cloud and AI solution sales for mid-market customers. Guides cloud transformation across infrastructure, data, and AI platforms; manages pipeline and forecasts; develops business cases and proofs of concept; collaborates with account executives, solution engineers, architects, partners, and customers; and drives opportunities from commitment through cloud consumption and deployment.

Define the vision, strategy, and roadmap for Microsoft’s Responsible AI platform. Lead development of capabilities for AI evaluation, red teaming, safety guardrails, risk detection, monitoring, governance, transparency, and compliance. Conduct enterprise customer discovery, translate emerging risks and regulations into scalable products, and coordinate execution across engineering, research, legal, security, compliance, and Microsoft product organizations. Establish success metrics, improve adoption, and represent Microsoft with customers, partners, standards bodies, and industry forums.

Conducts econometric, causal, statistical, and optimization analyses to improve operational efficiency, resource allocation, product performance, and business outcomes. The role defines efficiency measures, develops forecasting and optimization tools, partners with product and engineering teams on data instrumentation and implementation, and communicates findings to executives through clear reports.

Lead end-to-end data science projects: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, operationalize models at scale, run experiments, drive ethics/privacy, partner with customers and teams, and coach cross-disciplinary colleagues.

Lead end-to-end segmentation strategy for Microsoft Advertising, translating business priorities into coverage, capacity, and resource-allocation models. Build measurement frameworks, analytical models, and cross-functional alignment to operationalize segmentation into territory design, quota and capacity planning. Advise senior leaders and continuously refine models using data-driven insights to drive growth.

Leads technical pre-sales engagements for Microsoft Power Platform and low-code solutions. Develops customer win strategies, conducts technical discovery, designs solutions, delivers demonstrations and proofs of concept, and secures technical decision-maker endorsement. Builds executive and partner relationships, supports co-sell opportunities, communicates customer feedback to engineering and product teams, drives adoption, and provides technical leadership through workshops, training, mentoring, and community engagement.

Analyze AI training and inference workloads, build performance models and tools, evaluate hardware-software trade-offs, run silicon microbenchmarks, and guide architecture decisions for large-scale cloud AI systems. The role requires correlating models with measurements, diagnosing performance gaps, and communicating recommendations through technical reports and visualizations.

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.

Develop machine learning techniques focused on AI safety, alignment, and trustworthiness. Collaborate with product, research, and engineering teams to design, build, deploy, monitor, and iterate responsible AI systems at scale, from experimentation to production for large language models and distributed AI services.

Leads strategic financial services account strategy, executive relationships, complex enterprise sales, and revenue growth. Connects customer priorities with Microsoft AI, cloud, and digital capabilities while coordinating Microsoft specialists, customer success teams, partners, and stakeholders. Identifies strategic opportunities, manages forecasts and risks, influences decision-makers, and drives long-term account expansion and business outcomes.

Design, train, and evaluate Responsible AI components: fine-tune LLMs (including RLHF), build adversarial agent evaluations and safety mitigations, collaborate with engineering to deploy mitigations at scale, monitor operational performance, and troubleshoot end-to-end issues.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers to translate requirements into technical designs, drive engineering best practices (CI/CD, testing, observability), deliver end-to-end solutions, lead technical workstreams, and apply AI/LLM approaches where appropriate to produce production-ready outcomes.

Embed with strategic customers to lead end-to-end technical programs, applying AI-assisted engineering to accelerate delivery. Coordinate cross-functional teams, make data-driven decisions, manage risks, and cultivate reusable solution patterns and playbooks to scale impact.