Artificial Intelligence Jobs in Santa Clara, CA

Lead design and delivery of conversational and agentic AI solutions for client contact centers. Guide cross-functional teams to build NLP interfaces, prototype UIs, run usability testing, ensure data integrity and security, and advise clients strategically. Coach teams, manage large projects, and drive adoption of AI-powered contact center technologies to improve client experience and operational outcomes.

Lead design, build, and operation of scalable, secure AI-enabled platforms; mentor engineers; ensure reliability, security, and delivery of conversational AI and cloud-native solutions; collaborate cross-functionally to translate use cases into platform capabilities.

Lead Microsoft Dynamics 365 CRM implementations, architect solutions, manage project lifecycles and client accounts, mentor teams, ensure quality and post-go-live support, and drive innovation and continuous improvement.

Lead development and implementation of advanced AI/ML solutions, design and optimize models and algorithms, transform raw data into actionable insights, manage projects end-to-end, supervise and mentor teams, maintain quality and standards, and manage client engagements and expectations.

Lead AI governance projects within Risk and Compliance, assess governance/risk/control programs, translate technical concepts for non-technical stakeholders, design and evaluate AI governance frameworks and controls, interpret data to inform recommendations, build client relationships, and mentor junior team members.

Lead development and delivery of AI and GenAI solutions for health systems. Serve as strategic advisor, manage teams, ensure HIPAA-compliant deployments, implement MLOps and model governance, translate clinical workflows into AI use cases, and drive stakeholder alignment and operational excellence.

As a Software Development Engineer, you will create high-performance Linux software components, ensure system reliability, collaborate with teams, and design security features for containers in cloud environments.

Lead design, development, deployment, and support of large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and optimization to improve scalability, cost, latency, and throughput while guiding technical vision and cross-functional delivery.

Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.

Develop and evaluate ML and perception models for future sensing and autonomous driving. Work on detection, tracking, classification, sensor fusion, training pipelines, validation, robustness metrics, and integrate models into onboard systems while collaborating with cross-functional teams.

Lead end-to-end ML and perception efforts for future sensing in autonomous vehicles: design sensor architectures, multi-modal fusion, model development, metrics, simulation-driven evaluation, system integration, and production readiness while mentoring engineers and building scalable data and training infrastructure.

The Senior ML/AI Engineer will enhance developer productivity for AV engineers at GM by designing, implementing scalable, reliable systems and mentoring team members.

Lead design, build, and operate scalable GenAI platform components including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Collaborate cross-functionally, invent LLM optimization techniques, and shape long-term technical vision for foundational AI systems.

Lead go-to-market strategy, positioning, and field enablement for AI Protect. Build differentiated messaging, competitive intelligence, persona-driven content, and sales enablement assets to accelerate deal wins and translate product roadmap into market impact.

Lead design, build, and operate scalable observability systems for distributed cloud and on-vehicle environments. Contribute code and reviews, create technical designs, build tooling to collect observability signals, run PoCs for new tools, partner with engineering teams, define SLIs/SLOs, guide roadmap decisions, and mentor engineers to improve developer productivity and reliability.

Design, build, deploy, and support large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Collaborate cross-functionally, optimize model performance and cost, and contribute to technical vision and roadmap for foundational AI platforms.

Design and implement scalable, low-latency AI security infrastructure and high-performance networking code in Rust. Collaborate with product and cross-functional teams, debug complex network/system issues, and deliver secure, testable solutions for large-scale cloud security platform.

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

The role involves designing, developing, and supporting AI software components, leveraging various AI technologies, and optimizing performance for large-scale AI systems.

The role involves architecting a scalable AI platform, building distributed compute solutions, optimizing technologies, and mentoring internal talent in AI and ML.

As a Senior Lead AI Engineer, you will develop AI solutions, partner with cross-functional teams, optimize LLM performance, and contribute to the AI vision at Capital One.

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.

Design and build scalable AI platform capabilities to enable multi-step GenAI workflows, model execution, and integrations. Implement backend services, execution infrastructure, APIs, and observability to support production GenAI experiences across sales and product teams. Collaborate with AI engineers, data scientists, and product partners to turn AI use cases into reliable, extensible platform features.

Lead development and operation of CI platform components (RBE, FUSE) to enable scalable build, test, and developer workflows. Collaborate across teams, own projects end-to-end, drive engineering best practices, mentor engineers, perform design/code reviews, and support integration of internal tools with the FUSE-based file system to improve developer productivity for AV and ML workloads.

Serve as the field technical authority bridging enterprise AI and security: drive AI security strategy, lead demos and POVs, advise on LLM/RAG/agent risks and data protection, influence product roadmap, and create reusable enablement assets to scale sales and secure production AI deployments.