Artificial Intelligence Jobs in Santa Clara, CA

The Senior Client Engineer leads the design and management of client device solutions, focusing on MDM platforms JAMF and Intune, while mentoring teams and ensuring secure environments.

Lead hardware-software co-design to enable AI/HPC and agentic AI stacks on RISC-V CPUs. Integrate and optimize low-level kernel infrastructure, runtimes, distributed execution, memory systems, and developer tools, collaborating with architects, compiler engineers, and kernel developers to meet performance targets.

Leads and grows a software engineering team developing cloud software, data platforms, and AI-agentic products. Sets technical direction, guides architecture and design decisions, owns delivery roadmaps, partners cross-functionally, and maintains technical depth for hiring and incident review. Establishes AI-assisted development practices and a strong production reliability and on-call culture while mentoring engineers and supporting career development.

Lead presales for data and AI initiatives: design and present Microsoft Fabric-based data platforms, run discovery and AI workshops, scope proposals, translate technical designs into business value, mentor delivery, and support go-to-market and thought leadership.

Build and maintain an agentic platform that transforms high-stakes medical and legal casework into structured context. Work across the full stack: agent architectures, eval frameworks, data ingestion/indexing, and user-facing tooling. Ship workflows, design reliability-focused evals and guardrails, iterate with user feedback, and set patterns for AI-native development in a healthcare context.

Lead development of local AI agent frameworks and runtimes on Windows and GeForce RTX GPUs. Optimize agent inference, sandboxing, and privacy/security policies, collaborate with AI research and driver teams, mentor engineers, and deliver production-ready, local autonomous agent systems.

Own the strategy, roadmap, backlog, prioritization, and release planning for an enterprise Generative AI platform. Translate business requirements into scalable platform capabilities and engineering deliverables, while balancing value, usability, security, governance, and technical feasibility. Partner with AI Engineering, Data Science, Security, Privacy, Legal, Infrastructure, and business teams to drive adoption, reusable services, responsible AI practices, and measurable platform outcomes.

Develop and deploy LLM workflows and production machine learning models for nuclear-system design and analysis. Build surrogate models for real-time digital twins, manage data pipelines, maintain rigorous information controls, and lead AI initiatives from inception through delivery. The role also involves growing a software engineering team, presenting roadmaps and demos to leadership, gathering user feedback, and collaborating with nuclear engineers in a fast-paced startup environment.

Own Tenstorrent’s cloud sales segment from customer discovery through production deployment and revenue growth. Build pipeline, account strategies, forecasts, and a repeatable go-to-market motion for neoclouds, inference providers, model-as-a-service platforms, edge networks, and capacity aggregators. Identify differentiated AI workloads, lead technical evaluations and commercial negotiations, and partner with Product, Engineering, Field Applications, Marketing, and sales teams to drive adoption and strategic customer outcomes.

Leads supply chain data science and AI operationalization for Global Service Operations. Converts manual analytics into governed, automated AI-assisted workflows, taking solutions from prototypes to production with lineage, monitoring, lifecycle management, and ownership. Manages analysts, delivers against SLAs, develops statistical and machine-learning models, and communicates actionable insights across procurement, fulfillment, reverse logistics, inventory, and supplier operations. Measures cycle time, quality, and business impact while mentoring the team and advancing enterprise AI governance.

Own strategic account growth and quota-carrying sales for AI infrastructure and datacenter storage customers. Develop multi-year account plans, manage pipeline and forecasts, lead complex negotiations, and build executive relationships. Position WD storage technologies within software-defined, hybrid cloud, HCI, data protection, and scale-out architectures. Drive design-ins, customer qualification, platform standardization, new technology adoption, proof of concepts, and long-term supply commitments through cross-functional collaboration.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

The Forward Deployed Engineer interfaces directly with customers to assess and resolve security issues, delivering tailored AI and data-driven solutions, while documenting processes for broader application across customers.

As a Principal AI Engineer, you'll design scalable AI systems, mentor teams, develop large-scale LLMs, and optimize AI-driven cybersecurity solutions.

Design, develop, and implement AI/ML models, manage AI solutions on cloud platforms, and collaborate with teams to optimize models.

Lead 0→1 product development for Emerald Cloud Services: define vision, conduct customer discovery, set product requirements for AI compute provisioning and management, partner with engineering and GTM teams, and launch and scale cloud services for enterprise and AI customers.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

The Principal Digital Design Engineer will architect and implement complex digital designs for connectivity solutions, oversee micro-architecture and RTL implementation, and mentor junior engineers.

Embed with customers to learn their workflows, redesign and build production GenAI/LLM systems on AWS, ship and operate code, evaluate non-deterministic models, and own business outcomes.

Lead global commercial strategy and execution for AI infrastructure sales across data center, edge, and industrial markets. Own revenue targets, build strategic partnerships with hyperscalers/OEMs, lead complex deals, scale a global sales organization, and align cross-functional teams on product roadmaps, supply chain, and market expansion.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

Design, build, and deploy LLM-powered tools, RAG-based knowledge systems, and agentic workflows to automate SOC integration tasks. Own reliability, evaluation, and observability for AI systems and collaborate with SOCD teams to scope, validate, and measure productivity gains from deployed automation.