Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Designs, develops, deploys, and sustains Azure infrastructure for AI training and inference workloads. Responsibilities include coding, hardware and software integration, distributed systems, networking, GPU and cluster design, performance optimization, debugging, automation, test-driven engineering, documentation, partner collaboration, and on-call incident response. The role drives scalable, reliable infrastructure and mentors engineers while improving quality, maintainability, and customer outcomes.

Design and build Azure Kubernetes Service features and AI-native infrastructure, improve service reliability and developer velocity, automate incident prevention/remediation, integrate AI tools, and operate distributed, containerized systems at cloud scale.

Leads AI value creation and realization for strategic customer engagements. Runs CFO-focused workshops, develops value hypotheses and investment cases, builds ROI and P&L models, defines KPI measurement frameworks, and proves outcomes against baselines. Creates reusable value patterns, benchmarks, and playbooks while partnering with finance, strategy, engineering, delivery teams, and executive stakeholders to make AI investments measurable, fundable, and accountable.

Lead architecture and roadmap for Azure PostgreSQL systems; design and review scalable, maintainable database engine features (query processing, storage, transaction logging, recovery, versioning, IO, scale-out). Influence coding standards and run code reviews, write proof-of-concept or production code, contribute to open-source PostgreSQL/Linux, and participate in rotational on-call operations.

Join Azure PostgreSQL to design, implement, and test features in a relational database engine (query processing, logging, storage, IO, scale-out). Collaborate with stakeholders, write maintainable code, define test plans, operate live services (on-call), and contribute to open-source PostgreSQL and Linux.

Lead the architecture, development, testing, and deployment of hyperscale distributed storage systems optimized for AI and machine learning workloads. Drive innovations in scalability, performance, security, durability, and efficiency while collaborating with AI researchers and cloud infrastructure teams. Mentor engineers, guide technical strategy, and help shape Azure Blob Storage into an AI-native platform supporting zettabyte-scale storage.

Lead and develop a team of Technical Program Managers responsible for Azure fleet lifecycle and cloud expansion programs. Drive strategy, cross-functional alignment, roadmap execution, governance, dependency management, reliability, supportability, and operational excellence across engineering, operations, data science, and compliance teams. Use metrics, experimentation, automation, and Generative AI to improve platform performance and business outcomes while influencing executives and fostering an inclusive, high-performing culture.

Develop scalable data pipelines, statistical models, machine learning solutions, AI agents, dashboards, and decision-support tools for incentive compensation planning. Analyze large datasets, design quota and compensation models, evaluate business outcomes, ensure governance, and communicate recommendations to Finance, Engineering, product, sales, and executive stakeholders. The role also involves coding, debugging, automation, scenario modeling, and leading cross-functional analytical initiatives.

Owns and scales internal AI transformation solutions, workflow automations, operational tools, and business platforms. Responsibilities include managing technical program roadmaps, defining architecture and governance, integrating systems, coordinating troubleshooting and releases, establishing support models and documentation, improving AI-enabled workflows, and driving adoption. The role translates business needs into technical requirements and delivery plans while coordinating cross-functional stakeholders throughout the solution lifecycle.

Leads security solution sales by understanding customer needs, developing technical security solutions, conducting consultative conversations, and coordinating Microsoft and partner teams. Manages security pipelines, territory plans, forecasts, stakeholder mapping, cross-selling, upselling, and end-to-end opportunity execution. Advises customers on cloud security technologies, competitors, and solution strategies while driving licensing transactions, consumption, and business growth.