Artificial Intelligence Jobs in San Jose, CA

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

Own and execute a global strategic account plan for a major OEM. Build senior-level customer relationships and a global relationship map. Manage multi-product opportunity pipeline with accurate forecasting and CRM discipline. Deliver quarterly revenue, margin, and TAM share targets. Identify and develop new strategic sales opportunities and influence cross-functional teams. Leverage AI tools to enhance account strategy and execution.

Lead a global sales strategy and planning function to align account planning, market intelligence, and commercial planning with business unit goals. Drive annual and long-range sales planning, institutionalize strategic account planning, translate customer and market signals into actionable guidance, implement planning governance and metrics, and lead AI-driven commercial transformations while influencing senior executives and cross-functional partners.

Lead architect for Zscaler's AI ecosystem, integrating LLMs, vector DBs, and GPU infrastructure with Zero Trust. Own Secure AI roadmap to prevent data leakage, define APIs/SDKs and integration patterns, build developer and partner ecosystems, and drive cross-functional efforts to turn technical integrations into market-leading products.

Lead design, development, deployment, and support of scalable GenAI platform components (foundation model training, LLM inference, vector search, guardrails, evaluation, observability). Optimize training and inference performance, contribute to technical vision and roadmap, and partner with cross-functional teams to deliver responsible, production-grade AI systems.

Lead modernization of enterprise AI/ML infrastructure and analyst workflows. Build agentic, scalable, secure platform services, integrate generative AI and low-code/no-code tooling, scale AutoML for tabular and time-series, and engineer automated governance and controls while mentoring teams and influencing cross-functional stakeholders.

Lead strategy, development, deployment, and lifecycle of agentic AI platforms and infrastructure. Provide technical direction, build and grow engineering teams, set MLOps and orchestration best practices, align platform roadmap with business goals, ensure regulatory and ethical compliance, and drive adoption of scalable AI solutions across the enterprise.

Lead product management activities for commercial and internal software products across the lifecycle. Support large enterprise software implementations and program delivery, maintain program controls, report on risks and finances, mentor junior staff, manage stakeholder relationships, and align project objectives with strategic goals while driving continuous improvement.

Lead design and delivery of AI/GenAI solutions and scalable data infrastructure. Drive business development, manage multiple client engagements, mentor teams, implement AI models using Python and C++, ensure data quality, and promote innovation across projects.

Lead development and deployment of foundational AI systems: design, build, test, and support LLM training and inference, similarity search, guardrails, observability, and optimizations for scalability, cost, latency, and throughput while shaping technical vision and collaborating with cross-functional partners.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Lead an AI platform team to design, build, and deploy agentic, reusable AI services for healthcare payment integrity and clinical workflows. Provide technical and strategic leadership, drive deployment automation, CI/CD, production observability, ethical AI practices, and cross-functional partnership to ensure secure, scalable delivery and measurable business outcomes.

As a Staff Product Designer at FloQast, lead design strategy for AI-driven product capabilities, mentor teams, and ensure design consistency across platforms while enhancing user experiences and stakeholder communication.

As an Applied Researcher II, you will create AI systems for banking, working with cross-functional teams to develop and implement AI-powered products, while conducting applied research and engaging with emerging technologies.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Partner cross-functionally, invent LLM optimization techniques, and contribute to technical vision and roadmap for foundational AI infrastructure.

Lead a team to deliver AI powered products, leveraging machine learning and NLP for customer applications, while collaborating with cross-functional teams.

The role involves partnering with a team to deliver AI products, utilizing various technologies and conducting applied research to enhance customer experiences leveraging AI.

This role involves leading the development of AI-powered products, optimizing large scale AI systems, and mentoring cross-functional teams. It focuses on designing and deploying AI components, contributing to the technical vision, and applying cutting-edge AI techniques.

Lead design, build, deploy, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize production LLM performance (cost, latency, throughput) and contribute to long-term technical vision.

The role involves developing AI-powered products, conducting applied research, collaborating with a cross-functional team, and building AI foundation models. Candidates should be innovative, technical, and have a deep understanding of AI methodologies.

Lead design, development, deployment, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI performance (cost, latency, throughput), partner cross-functionally, and contribute to technical vision and roadmap.

As an Applied Researcher I, you will partner with a cross-functional team to develop AI-powered products, build AI foundation models, and conduct high-impact applied research in machine learning.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

As an Applied Researcher I, you'll partner with cross-functional teams to deliver AI-powered products, build foundation models, and engage in applied research on advanced AI techniques.

Lead cross-functional teams to develop and deploy AI-powered products, improve AI system performance, and create innovative AI solutions at Capital One.