Artificial Intelligence Jobs in San Jose, CA

Lead AI Engineer responsible for developing AI-powered products, optimizing large language model inference, and collaborating across teams to enhance customer interactions and business value.

Lead design, build, deploy, and support foundation model training and LLM inference systems, similarity search, guardrails, evaluation, and observability. Optimize production AI for scalability, cost, latency, and throughput. Collaborate cross-functionally, mentor engineers, and shape long-term foundational AI technical vision and roadmap.

Lead AI Engineer responsible for designing and developing AI-powered products, utilizing ML algorithms, and optimizing large-scale AI systems. Collaborate with cross-functional teams to enhance customer experience and drive AI initiatives at Capital One.

Leads SSD enablement, qualification, validation, and production readiness for NVIDIA, AMD, and other AI platforms. Coordinates customer and internal engineering teams to resolve hardware, firmware, PCIe/NVMe, thermal, power, performance, and interoperability issues. Identifies emerging AI storage workloads, conducts feasibility studies and proof-of-concepts, evaluates ecosystem trends, and develops future product opportunities.

Architect and build device-side telemetry, generative AI agents, predictive analytics, and autonomous network platforms. The role develops RAG and agentic AI solutions for proactive troubleshooting, root cause analysis, anomaly detection, and closed-loop remediation. It also leads multi-cloud data architecture across AWS and GCP, edge model deployment, MLOps/LLMOps, governance, and production collaboration with network, data science, and product teams.

Develop scalable data pipelines, analytics platforms, and machine learning infrastructure. Build and maintain software tools supporting AI-driven platforms, distributed data systems, and reliable analytics capabilities. Apply programming, data structures, algorithms, cloud technologies, machine learning frameworks, and distributed systems concepts while collaborating across Cisco business groups. This internship is intended for students enrolled in a degree or workforce development program.

Architects and delivers enterprise integration and API platforms using event-driven, asynchronous, cloud, and AI-augmented workflows. Develops reusable frameworks across SAP, SaaS, and partner ecosystems; governs APIs; integrates EDI, REST, GraphQL, and SOAP systems; and builds autonomous, self-monitoring and self-healing workflows. The role also requires programming, identity and access control expertise, CI/CD automation, observability, and close collaboration with Product and Engineering teams.

Develop production AI-powered systems that improve software quality, engineering productivity, debugging, and developer workflows. Build intelligent services involving code analysis, retrieval, orchestration, evaluation, monitoring, and large-scale engineering data. Partner across teams to translate workflow challenges into reliable AI solutions, evaluate models and frameworks, and optimize quality, latency, cost, and reliability from concept through deployment and continuous improvement.

Lead technical engagement for AI training and infrastructure at scale. Collaborate with engineering teams and customers to ensure successful deployment and optimization of AI/ML solutions.

Lead the architecture and development of Jerry.ai’s next-generation AI agents and workflow automation platform. Build conversational and computer-use agents, document validation, voicebot interactions, and integrations with external insurance systems. Evaluate emerging AI technologies, deploy production LLM systems, and improve reliability, latency, cost, evaluation, and failure handling. Partner with OpenAI on next-generation voice models and automation capabilities.

Lead the architecture and development of Jerry.ai’s next-generation AI and automation platform. Own conversational agents, voicebots, computer-use agents, backend workflow automation, document validation, transaction orchestration, and external insurance-system integrations. Evaluate emerging AI technologies, deploy production LLM systems, and partner with OpenAI on advanced voice and workflow solutions. The role requires end-to-end software ownership, strong architectural judgment, and experience managing evaluations, regressions, latency, cost, and failure handling.

Lead the architecture and production deployment of next-generation AI agents and workflow automation. Own conversational interfaces, voicebots, computer-use agents, document validation, transaction orchestration, and external system integrations. Evaluate emerging AI technologies, optimize LLM systems for reliability, latency, cost, and failure handling, and partner with OpenAI on advanced voice and automation models.

Lead the architecture and development of Jerry.ai’s next-generation AI agents and workflow automation platform. Own conversational interfaces, voicebots, computer-use agents, document validation, transaction orchestration, and integrations with external insurance systems. Evaluate emerging AI technologies, deploy production LLM systems, and partner with OpenAI on next-generation voice and automation capabilities. The role requires end-to-end software ownership, attention to evaluation, latency, cost, reliability, and failure handling.

Develop, test, deploy, and support AI-powered applications, automation solutions, and agent-based systems. Translate stakeholder workflows into scalable technical solutions using Python, C#/.NET, TypeScript, React, Azure AI services, APIs, and orchestration frameworks. Implement RAG, prompt engineering, and agent workflows; maintain testing, documentation, security, monitoring, and support standards. Collaborate with engineering, architecture, legal, security, data, and business teams while contributing to pilots, user adoption, and continuous improvement.

Develop and maintain prompts, responses, and datasets for large language models. Lead labeling initiatives with internal teams and third-party firms, create stakeholder guidelines, and train teams on LLM and dataset development best practices. The role requires native-level English, bilingual proficiency in an additional language, specialized domain knowledge, and a college degree or equivalent experience.

Lead system-level architecture for connecting XPUs to memory and interconnect fabrics across node, rack, and cluster scales. Define topology and communication strategies for distributed LLM training and inference, resolve integration issues across silicon, networking, memory, and software teams, and mentor system-interconnection architects. The role requires substantial NPU architecture, ASIC tapeout, silicon bring-up, validation, and production deployment experience.

Identify enterprise AI opportunities, evaluate emerging models and platforms, build prototypes and proofs-of-concept, quantify business value, and present recommendations to technical and executive stakeholders to drive AI adoption across the company.

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

Build and scale the infrastructure layer for visual intelligence: optimize VLM inference and GPU serving, design multimodal APIs and structured outputs, ensure scalable backend systems, reliability, observability, CI/CD, and developer experience. Drive 0→1 product work with strong testing discipline, schema validation, and performance optimization.

Manage major infrastructure projects in the energy sector focusing on electric transmission and substation upgrades, ensuring quality and stakeholder satisfaction.

Design, develop, debug, and document complex software for semiconductor equipment components and devices. Create test procedures, specifications, and test plans for simulators, test benches, and lab environments. Troubleshoot software issues, implement fixes, analyze requirements, coordinate schedules, and communicate with internal and external customers. The role applies software engineering, machine learning, and AI concepts to semiconductor and display technology solutions.

The Director of Segment Marketing will drive strategy for cloud infrastructure and financial markets, advocate for customers, build partnerships, and elevate marketing efforts to advance Arm's leadership in data center computing.

Serve as senior technical advisor to strategic partners for Arm-based Edge AI SoC solutions. Lead system-level architecture, IP selection, integration, optimization, technical engagements, demonstrations, and cross-functional resolution to drive design wins and product adoption while providing customer feedback to influence product roadmaps.

Lead and scale teams building ServiceNow's AI evaluation platform. Define strategy and roadmap for benchmarks, automated scoring, verifier systems, and quality monitoring. Deliver unified internal and customer-facing evaluation services with APIs and dashboards. Drive novel evaluation methods, safety assessment, and cross-functional collaboration to ensure reliable, production-grade AI quality.

Lead a team building evaluation infrastructure and benchmarks for agentic and generative AI. Design automated tests, validate RAG pipelines, benchmark frontier LLMs, and translate evaluation results into product and risk recommendations to ensure reliable, safe, and cost-effective autonomous workflows.