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

Leads enterprise AI enablement product strategy and development, including internal AI infrastructure, autonomous agents, RAG systems, semantic layers, integration capabilities, governance, evaluation pipelines, and responsible AI guardrails. Drives workflow transformation, adoption, change management, cross-functional alignment, and feedback loops across engineering, finance, legal, and business teams.

Leads applied AI research and strategic direction for foundation models and large-scale machine learning systems. Responsibilities include designing, training, evaluating, validating, and deploying models; advancing research in areas such as LLMs, optimization, self-supervised learning, robustness, and explainability; guiding applied scientists and managers; collaborating with engineering, product, and academic partners; and translating research into scalable customer-facing products.

Leads applied AI research and strategic direction for foundation models and large-scale machine learning systems. Partners with scientists, engineers, and product leaders to design, train, evaluate, validate, and deploy AI models. Defines long-term research priorities, advances state-of-the-art methods, mentors applied scientists and managers, collaborates with academia, and represents Capital One in the research community.

Leads the vision, strategy, roadmap, architecture modernization, governance, and team growth for Capital One’s AI Assistance platform and Eno chatbot. Partners with product, engineering, data science, design, and risk teams to deliver customer-focused digital financial experiences, manage AI/ML risks, and achieve measurable business outcomes.

Design, develop, deploy, and optimize production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead multi-model orchestration and cost-performance optimization across cloud infrastructure. Establish AI engineering standards, guide technical roadmaps, lead design reviews, and mentor senior AI engineers while integrating research advancements into scalable, responsible products.

Design, develop, deploy, and support enterprise AI systems, including foundation models, LLM inference, agentic workflows, vector search, model evaluation, governance, and observability. Establish AI architecture standards, optimize model performance, cost, latency, and scalability, and lead model routing and orchestration initiatives. Drive responsible AI practices, contribute to technical roadmaps, mentor engineering teams, and influence cross-functional stakeholders and enterprise AI strategy.

Leads data science for enterprise agentic AI products, developing and deploying machine learning models, designing experiments, analyzing telemetry, and translating findings into business strategy. Partners with data scientists, AI/ML engineers, and product managers while guiding large-scale analysis across numeric and textual data. The role also requires technical leadership, stakeholder communication, innovation, talent development, and expertise in statistical modeling, deep learning, and cloud-based data science.

Leads technical vision and software architecture across Capital One, designing scalable cloud, data, microservice, and event-driven solutions. Drives modernization, defines platform and API standards, ensures technical quality, leads cross-divisional initiatives, and mentors engineers. Requires deep experience in software engineering, enterprise architecture, cloud computing, data architecture, distributed systems, web technologies, databases, networking, and full lifecycle delivery.

Designs, develops, deploys, and optimizes enterprise AI systems, including foundation models, LLM inference, agentic workflows, similarity search, model routing, and observability. Establishes AI architecture standards, improves system cost and performance, champions responsible AI, and leads technical direction, mentorship, and cross-functional collaboration across Capital One.

Lead technical vision and architecture for Card Tech while remaining hands-on as a player-coach. Design scalable, secure systems; modernize monoliths into microservices and event-driven platforms; establish API and engineering standards; mentor engineers; evaluate AI-generated code; and drive cross-divisional technical initiatives. The role requires expertise in cloud computing, data architecture, distributed systems, enterprise architecture, software development, and strategic use of agentic AI tools.