Artificial Intelligence Jobs in Sunnyvale, CA

Lead technical engagements with strategic ISV partners to design, prototype, and ship production agentic and generative AI systems. Drive adoption of NVIDIA stack (NeMo, TensorRT-LLM, etc.), set account objectives and timelines, coordinate cross-functional teams, and feed partner insights into Product, Engineering, and Research to shape roadmaps and deliver scalable enterprise deployments.

Lead strategy and roadmap for AI-powered personalization and content ranking across Edge, Windows, Copilot, and partners. Define representation, retrieval, features, objectives, training, evaluation, and serving for recommendation and personalization systems. Drive evaluation, experimentation, and cross-team integration; set quality bars, privacy and policy guardrails; align VP-level stakeholders and influence resource allocation to build scalable personalization and ranking platform capabilities.

Lead competitive strategy for Microsoft's AI and cloud infrastructure products, evaluating accelerators, CPUs, memory, networking, storage, and rack-scale systems. Analyze technology roadmaps, performance, power, cost, supply, utilization, and total cost of ownership. Partner with architecture, engineering, finance, sourcing, and product teams to develop data-driven recommendations, competitive assessments, dashboards, and executive-level insights influencing Azure product roadmaps and investment decisions.

Define long-term architecture and technical strategy for Target's enterprise ML/Ops platform. Design cloud-native, scalable, secure Kubernetes-based platforms; establish ML lifecycle, deployment, governance, observability, and responsible AI standards; evaluate technologies; mentor engineers; and partner with infrastructure, security, and product teams to modernize platform capabilities.

Design, deploy, and operate distributed backend systems supporting large-scale, low-latency machine learning inference. Lead inference platform direction, optimize high-throughput serving infrastructure, collaborate with ML engineers, and ensure production reliability through monitoring and observability. Manage GCP cloud infrastructure and Kubernetes workloads while applying DevOps, SRE, testing, deployment, and security best practices.

Own the strategy, architecture, evaluation, and production delivery of Jerry.ai’s AI agents and workflow automation platform. Lead chatbot, voicebot, computer-use agent, document validation, transaction orchestration, and external system automation initiatives. Evaluate emerging AI technologies, make technical investment decisions, partner with OpenAI, and collaborate closely with engineering and prompt engineering teams. The role requires hands-on experience launching LLM systems and managing evaluations, regressions, latency, cost, and failure handling.

Own the strategy, architecture, evaluation, and production deployment of Jerry.ai’s next-generation AI agents and workflow automation platform. Lead conversational agents, voicebots, computer-use agents, document validation, transaction orchestration, and external insurance-system integrations. Evaluate emerging AI technologies, make technical investment decisions, partner with engineering and OpenAI, and ensure systems meet requirements for reliability, latency, cost, regression prevention, and failure handling.

This role involves developing and maintaining CI/CD pipelines, enhancing deployment processes, ensuring infrastructure reliability, and promoting best practices within the AIDR platform team.

Design and build NVIDIA’s enterprise AI agent platform, including agent blueprints, runtime safety and policy enforcement, multi-agent orchestration, credential brokering, checkpointing, observability, evaluation, and self-improvement loops. Deploy reliable long-running services at scale, integrate enterprise systems, support secure execution, and participate in on-call operations. The role requires extensive distributed systems or infrastructure experience and hands-on agent development.

Leads complex government AI deployments from pre-sale discovery through production adoption, overseeing client relationships, delivery planning, cross-functional execution, change management, and executive communication. Translates agency workflows into technical requirements, manages risks and dependencies, drives measurable outcomes, and converts deployment feedback into product improvements. Builds deployment playbooks, operating cadences, and future delivery teams while supporting renewals and expansions. Requires strong AI/ML and enterprise systems fluency, senior stakeholder leadership, and 30–50% travel.

Designs and operates secure AI applications and backend microservices on AWS. Responsibilities include threat modeling, secure design reviews, vulnerability remediation, secure API development, AI guardrails, prompt testing, RAG pipelines, monitoring, audit logging, and incident readiness. The role collaborates with engineering, product, cloud infrastructure, and security teams to embed secure-by-design practices throughout the software development lifecycle.

Own the quality strategy and release gate for Unity’s Gaming AI organization. Build AI-native testing, evaluation, defect intelligence, test automation, and quality measurement systems across frontend, backend, and dependent systems. Establish methods for evaluating nondeterministic AI outputs, including correctness, latency, cost, and consistency. Lead through influence across engineering, art, and product while connecting quality investments to creator and player outcomes and making evidence-based release decisions under schedule pressure.

Leads the design, development, and deployment of scalable, reliable software and infrastructure solutions. Builds AI agents, automation workflows, observability integrations, and monitoring systems using technologies including C++, Python, Java, Claude, Codex, BigPanda, ITMP, and Prometheus. Collaborates across teams, drives engineering standards, mentors junior engineers, and manages complex end-to-end projects.

Manage customer-facing software and AI delivery projects from initiation through closure. Build project plans, coordinate technical and business teams, communicate status and risks to enterprise customers and executives, support escalations, and improve PMO practices. The role also involves mentoring team members, evaluating AI use cases and data readiness, tracking AI-specific risks, and setting realistic expectations for conversational AI and generative AI deployments.

Build the enterprise platform for an AI creative product, including workspaces, permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services, APIs, and polished React/Next.js administrative interfaces for multi-tenant customers. Collaborate with founders, sales, and customers to define and ship enterprise features while taking increasing ownership of platform surfaces.

Build the enterprise platform for an AI creative product, including workspaces, roles, permissions, SSO, audit logging, usage-based billing, invoicing, and payment infrastructure. Design scalable APIs and multi-tenant architectures, strengthen security and reliability, and create React/Next.js administrative experiences. Partner with founders, sales, and customers to deliver enterprise requirements, establish engineering practices, and help shape the enterprise engineering team.

Lead strategy and execution for an AI-native product-led motion across AI-native ITSM. Own customer journeys from discovery to enterprise adoption, build telemetry and experimentation frameworks, design onboarding and in-product guidance, develop PQL models, and drive cross-functional initiatives to increase activation, adoption, expansion, and revenue.

Lead large-scale SRE initiatives, define reliability and platform roadmaps, and build resilient distributed systems for AI-driven products. Design AI agents and skills for platform operations, improve automation and observability, and collaborate across cloud, security, platform, and AI/ML teams. Troubleshoot complex systems, drive incident and postmortem practices, and mentor engineers. The role requires deep expertise in systems architecture, networking, Kubernetes, public cloud, infrastructure as code, and automation.

Build and operate production-grade AI, data, and distributed systems for fraud intelligence. Responsibilities include real-time data pipelines, high-throughput architecture, LLM-powered agentic workflows, AI tooling, rule and label automation, ML pipeline productionization, privacy safeguards, and cross-functional collaboration. The role requires strong Python engineering, distributed systems, cloud infrastructure, big data technologies, and machine learning fundamentals.

The role involves architecting AI applications, delivering scalable solutions, conducting research, and implementing high-quality code for cloud platforms. Requires collaboration and effective communication.

Develops Microsoft’s executive AI transformation narrative for Chief AI Officers, CIOs, and business leaders. Owns thought leadership and content strategy across digital, event, and executive engagement channels; translates AI capabilities into business outcomes and adoption guidance. Uses customer research, market intelligence, engagement data, and experimentation to optimize messaging and content experiences. Partners cross-functionally with product, engineering, sales, research, web, UX, and creative teams to drive enterprise-scale Copilot adoption.

Lead architecture, bring-up, validation, optimization, and deployment of networking infrastructure for large-scale AI training and inference. Define networking requirements, design Layer 3/4 and RDMA/AI fabric solutions, develop validation and observability tooling, perform packet-level debugging and root-cause analysis, and collaborate across silicon, firmware, software, and Azure teams to ensure performance, scalability, and reliability of hyperscale AI clusters.

Leads cross-functional AI Platform programs supporting autonomous vehicle verification, validation, reliability, and driverless readiness. Owns reliability metrics, execution plans, issue triage, testing priorities, risk assessments, and leadership updates across systems, software, hardware, autonomy, data science, and vehicle operations teams. Translates field failures into engineering priorities and improves troubleshooting, validation, and recovery workflows.

Designs and delivers AI-augmented enterprise integration platforms, API ecosystems, and autonomous workflows. Responsibilities include developing event-driven distributed systems, integrating SAP and SaaS applications, managing API lifecycles, supporting EDI deployments, implementing secure identity and access controls, and building CI/CD and observability capabilities. The role uses agentic AI, workflow automation, and intelligent monitoring to enable self-healing, adaptive integration across cloud and enterprise environments.

The AI Marketer/DevRel will enhance brand awareness through technical content, community engagement, and storytelling while fostering developer relations.