Top Tech Jobs & Startup Jobs in San Francisco, CA

Develop causal economic analyses and econometric models using Mastercard and public datasets. Translate business questions into identification strategies, lead projects from data ingestion through validation and communication, apply causal machine learning and experimentation methods, prototype scalable analytics, guide scientific best practices, and present findings to clients and nontechnical stakeholders.

Leads Mastercard’s North American commercialization strategy for BVNK-powered digital asset and stablecoin payment solutions. Drives enterprise sales, strategic partnerships, pipeline development, revenue growth, market expansion, and executive client engagement across financial institutions, fintechs, payment providers, merchants, marketplaces, and other digital economy participants. Partners with product and regional sales teams to prioritize use cases, inform roadmaps, and accelerate adoption of cross-border payments, remittances, payouts, treasury, B2B payments, and wallet solutions.

Leads Mastercard’s global AI Engineering organization within the AI Center of Excellence. Oversees the delivery and scaling of enterprise AI products, agentic AI solutions, reusable AI assets, and intelligent automation from design through production. Partners across engineering, infrastructure, data, security, risk, architecture, product, and business teams to ensure secure, reliable, governed, and measurable outcomes. Builds high-performing global teams and drives adoption, operational excellence, responsible AI, and production readiness in a regulated environment.

Leads product strategy, roadmap, and execution for Mastercard’s Agent Pay for Machines protocols and standards. Partners with engineering, architecture, legal, compliance, security, commercial, and external ecosystem stakeholders to develop secure, scalable payment integrations. Translates market and partner needs into technical requirements, documentation, and delivery plans; represents Mastercard in standards forums; and evaluates emerging technologies including agentic commerce, blockchain, digital assets, and programmable payments.

Architect and engineer secure, scalable enterprise AI infrastructure supporting LLM training and inference, machine learning, agentic AI, and production platforms. Lead HPC, GPU, Kubernetes, cloud, networking, storage, reliability, observability, security, governance, and automation efforts. Evaluate emerging technologies, drive architecture and engineering standards, lead cross-functional initiatives, and mentor engineers in a highly regulated environment.

Owns business development and account sales for Mastercard Services across commercial, fintech, and digital partnership clients. Responsibilities include achieving revenue targets, managing executive relationships, refining solution value propositions, leading pitches, coordinating cross-functional teams, setting territory strategy, and managing the end-to-end sales process from prospecting through contract execution.

Leads software engineering strategy, architecture, execution, and organizational growth for Mastercard’s AI-native decisioning platform. Oversees scalable distributed systems, streaming, AI, and cloud-native technologies; partners with Product, Architecture, AI, and Platform Engineering; drives technical excellence, reliability, security, and business outcomes; and recruits, mentors, and develops high-performing engineering teams.

Design, build, validate, and deploy machine learning models; perform EDA and statistical analysis; design and maintain scalable ETL/ELT data pipelines; work with large distributed datasets; run A/B tests; monitor production model performance; partner with product, engineering, and business teams to deliver data-driven solutions and ensure data quality.

Lead partner recruitment, onboarding, activation and growth for Mastercard Media Solutions in NAM. Build territory and joint business plans, manage channel pipelines, hit revenue quotas, enable partners, coordinate internal stakeholders, and provide market feedback to product and marketing teams.