Top Tech Jobs & Startup Jobs in San Francisco, CA

Own the long-term strategy, roadmap, and cross-organizational execution for AI agent authoring and lifecycle experiences. Define unified capabilities for creation, publishing, evaluation, observability, governance, versioning, operations, and support across Microsoft platforms. Use customer research, telemetry, market intelligence, and AI insights to prioritize investments and improve product outcomes. Lead complex product and architecture decisions while aligning executives, engineering, design, marketing, and partner teams.

Leads strategic business planning for Microsoft's gaming advertising business, including opportunity sizing, business cases, demand and supply planning, requirements documentation, competitive intelligence, and monetization strategy. Manages cross-functional workstreams, timelines, dependencies, governance, and stakeholder communications. Partners with Product, Engineering, Operations, Finance, and Sales to prioritize initiatives, develop recommendations, and drive plans through delivery using data, market research, customer insights, AI, and automation.

Own the strategy, design, launch, scaling, and lifecycle management of commercial offers for regulated and sovereign markets. Translate regulatory, customer, and operational requirements into scalable offerings, pricing, packaging, support models, and delivery frameworks. Partner cross-functionally with engineering, finance, sales, delivery, security, legal, marketing, and customer success. Drive market insights, AI-enabled innovation, portfolio economics, compliance by design, field readiness, adoption, and operational execution across commercial and government cloud environments.

Leads the operating model for Microsoft Unified foundational offers across support, customer success, and engineering. Owns portfolio taxonomy, revenue attribution, demand and capacity modeling, pricing architecture, investment prioritization, governance, and scorecards. Influences senior cross-functional leaders to improve margins, retention, customer value, upgrades, delivery economics, and investment returns without direct authority.

Develop machine learning techniques for AI safety, alignment, and trustworthy AI. Collaborate with research, product, and engineering teams to design, build, deploy, monitor, and continuously improve responsible AI systems and LLM-based services at scale.

Defines strategy, roadmap, and platform capabilities for Responsible AI across the AI lifecycle. Leads development of evaluations, red teaming, guardrails, risk detection, monitoring, governance workflows, transparency, and provenance. Partners with engineering, research, security, legal, compliance, and enterprise customers to translate emerging risks and regulations into scalable products. Drives customer discovery, cross-organizational execution, success metrics, adoption, and industry engagement for trustworthy AI capabilities.

Leads a team of AI solution specialists serving complex enterprise customers. Responsibilities include executive engagement, AI transformation strategy, consultative solution sales, pipeline and forecast management, partner development, customer adoption, business planning, and coaching high-performing teams to deliver measurable outcomes using Microsoft AI solutions.

Leads responsible AI programs for high-impact models, products, and use cases. Evaluates AI risks, architectures, and mitigation effectiveness; develops scalable policies, governance processes, and requirements; manages cross-functional implementation across engineering, research, sales, and policy teams; supports incident response; and drives accountability for responsible AI throughout product development and release lifecycles.

Build and operate autonomous cloud operations capabilities for Microsoft's Kubernetes fleets. Design distributed platform and orchestration services enabling AI agents to execute deployment, resiliency, recovery, and optimization workflows. Implement safety controls, observability, evaluations, and rollback mechanisms. Own features from design through production, investigate incidents, improve reliability, make architectural decisions, and mentor engineers.

Lead and negotiate high-value, technically complex finance data partnerships across exchanges, indexes, prediction markets and aggregators. Align Product, Engineering, Legal, Finance and leadership to structure AI/ML and API-based deals, manage regional coverage, optimize portfolio strategy, and represent work to executives.