Artificial Intelligence Jobs in Sunnyvale, CA

Build and enhance internal ML tooling to analyze and optimize model distillation, training, and inference. Collaborate with AV engineering and hardware teams to profile performance on GPUs and in-car compute, develop workflows for correctness and efficiency, trace distributed training jobs, and influence model architecture decisions.

The Director of Business Development at CoreWeave will lead and manage strategic partnerships within the AI and Cloud ecosystems, focusing on revenue generation and market expansion through new joint offerings and integrations.

Lead design and delivery of production autonomous agents and agentic workflows: architect orchestration, integrate and optimize frontier LLMs, drive model fine-tuning and evaluation, mentor engineers, and translate business goals into safe, reliable, scalable AI-powered product experiences.

The role involves leveraging Microsoft Dynamics technologies to solve client business issues, managing projects, and delivering solutions in a consulting capacity.

As a Senior Associate, you'll leverage Dynamics 365 applications to craft solutions, analyze complex problems, mentor team members, and manage project tasks tirelessly while strengthening client relationships.

The Specialist Seller will drive go-to-market execution for AI Products, architecting deals, building partnerships, and developing success metrics for customer adoption while collaborating with teams for growth. Requires extensive experience in enterprise sales and AI-based selling.

Lead the design and implementation of Microsoft Dynamics 365 solutions, mentor team members, manage projects, and enhance client relationships to achieve operational efficiency.

Lead large-scale Microsoft Dynamics 365 CRM projects, provide strategic guidance, innovate processes, and coach teams while engaging senior clients to achieve operational excellence.

As a Manager, you will supervise teams, manage client engagements, and facilitate the implementation of Dynamics 365 ERP Finance. This includes analyzing complex business issues and ensuring adherence to methodologies and standards.

Lead the design and implementation of Microsoft Dynamics ERP solutions, manage large-scale projects, and innovate processes to enhance operational efficiency and client outcomes.

Design, build, and operate production-grade Java and Python microservices for AI-native features. Own APIs, distributed systems, Kubernetes deployments, AI model integrations, observability, and technical leadership across cross-functional teams.

Design and build scalable microservices and platforms for AI security event processing, mentoring team members, and ensuring operational excellence.

As a Principal Product Manager, guide development of AI-powered employee experiences, collaborating with teams to create impactful products, translate user feedback, and stay updated on AI trends.

Design, build, and operate production-grade agentic AI systems: multi-agent orchestration, enterprise-grounded reasoning using CMDB/Knowledge Graph, retrieval/RAG pipelines, model integration with frontier SDKs, and trust/safety/governance. Lead architecture, code quality, and mentor engineers for scalable, safe autonomous agents.

Design, train, evaluate, and productionize LLM-based NLU and agentic AI systems. Improve model quality, latency, reliability, and safety; fine-tune models, implement agent architectures, and collaborate across teams to deploy scalable, privacy-preserving conversational AI.

Design, build, and productionize agentic AI systems (agent orchestration, sandboxed execution, latency optimization, agent memory, LLM self-reflection, knowledge graphs, multimodal I/O). Ship scalable, production-grade code, mentor engineers, and collaborate with ML, security, product, and UX teams to deliver enterprise AI features.

Lead strategy and execution for the Vault data & AI security product bundle, owning roadmap, cross-functional coordination, regulatory compliance, encryption, code signing, log export, and AI-native security features to scale monetizable, enterprise-grade security capabilities and drive adoption.

Lead and scale teams to build and operate an AI evaluation platform for internal and customer use. Define strategy and roadmap for benchmarks, automated scoring, verifiers, and monitoring. Drive new evaluation methodologies, architect unified APIs and dashboards, and collaborate with product, engineering, and research to ensure AI quality, safety, and reliability.

Lead delivery of AI-driven property & casualty insurance operations solutions: analyze client needs, design and implement software and AI architectures, manage projects and teams, coach staff, run training, ensure adoption, and drive process innovation while maintaining governance and standards.

The Senior Manager of Embodied AI will oversee AI/ML engineering teams, manage operational excellence in data scaling for autonomous vehicles, and collaborate across teams to improve performance and innovation in AV technology.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Design and build AI agents, first-party web and mobile apps, and scalable backend services. Integrate LLM frameworks and enterprise systems, implement APIs and microservices, ensure observability and security, and collaborate with Finance, Security, and Engineering stakeholders.

Partner with the SVP/GM to drive strategy and execution for Employee Experience & AI. Lead cross-functional alignment, manage high-impact initiatives, represent the executive externally, set meeting agendas and communications, and deliver special projects while operating with technical fluency in AI and strong operational rigor.

The AI Governance Manager at PwC will lead teams in assessing governance and risk frameworks, mentor junior staff, and enhance project delivery through innovative methodologies. The role involves maintaining compliance standards and building client relationships using advanced analytics and technology resources.

Design and build production-grade full-stack, AI-enabled applications. Develop React/Next.js frontends, backend services on Kubernetes, integrate LLM/AI features, connect data platforms, implement CI/CD, automated testing, observability, and ensure secure, high-performance APIs and services.