Senior Director, Enterprise AI & Automation

Who We Are Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. What We Offer Salary: $224,000.00 - $308,000.00 Location: Santa Clara,CA You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more. At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits. Position Overview Applied Materials is seeking a visionary engineering leader to drive the enterprise-wide strategy and execution of AI, Generative AI, Agentic Automation, MLOps, and Robotic Process Automation (RPA) capabilities. Reporting to the VP of Engineering, this leader will own the full AI/GenAI lifecycle—from ideation and PoC through production deployment and enablement—while leading cross-functional teams, influencing senior stakeholders, and building a culture of innovation and responsible AI use. Key Responsibilities Strategic AI & GenAI Leadership Own the Enterprise AI/GenAI strategy and PoC-to-production delivery across domains (Contract Analytics, Quality, Finance, Supply Chain), aligning investments with business priorities. Architect and govern the Enterprise Agentic AI Strategy, deploying multi-agent frameworks and LLM-powered tools at scale. Drive fine-tuning, prompt engineering, and domain adaptation of LLMs for Applied Materials’ use cases; contribute to AI governance and commercialization at the executive level, and represent the organization at industry conferences (e.g., ET India, EPTC Singapore). Enterprise LLM Platform & Multi-Cloud AI Infrastructure Enable secure enterprise access to 100+ LLMs across Azure AI Foundry, AWS Bedrock, and GCP Vertex AI, integrating open-source models via artifact platforms (e.g., JFrog). Partner with Security, Legal, and Infrastructure to streamline PoC cycles, standardize sizing, and ensure compliant AI deployment. Enable autonomous AI environments and MCP (Model Context Protocol) servers for internal tools and agentic workflows. MLOps & Model Lifecycle Management Lead end-to-end MLOps programs — training pipelines, CI/CD for ML, feature stores, and production monitoring — and drive modernization of ML infrastructure (e.g., CDSW → Databricks). Establish model governance (bias detection, explainability, drift monitoring, retraining) and champion Databricks best practices across data science and engineering teams. Agentic AI & Automation Architect and deploy enterprise-grade multi-agent AI systems for complex, multi-step workflows, integrating with ERP, CRM, and ITSM to automate high-value decisions end-to-end. Design internal AI tools and agents (e.g., AI Finance Bot, domain-specific LLM applications) and lead the roadmap for next-generation agentic platforms as emerging capabilities mature. Robotic Process Automation (RPA) Lead the RPA Center of Excellence and enterprise-scale automation programs, delivering measurable cost avoidance ($100M+ annually) and operational efficiency gains. Champion modern RPA platforms (UiPath AutoPilot) and AI-augmented tooling; expand automated ticket resolution to 60%+ of support requests. Establish RPA governance, change control, and operational KPIs to sustain reliability and scalability of the automation estate. Required Qualifications Experience 15+ years in software engineering, data science, or AI/ML, with 7+ years leading large engineering or AI teams. Track record delivering enterprise-scale AI/GenAI programs with measurable business impact, and building/scaling production MLOps platforms. Experience deploying RPA programs at scale (UiPath, Blue Prism, Automation Anywhere, or equivalent) and hands-on with agentic AI frameworks (LangChain, AutoGen, CrewAI, or comparable). Experience leading governance, legal, and security review processes for AI/GenAI deployments in regulated or enterprise contexts. Technical Skills Deep LLM expertise: fine-tuning, prompt engineering, RAG architectures, and domain adaptation. Multi-cloud AI platforms (Azure AI Foundry, AWS Bedrock, GCP Vertex AI) and MLOps tooling (Databricks/MLflow, Kubeflow, SageMaker, or equivalent), with model monitoring and drift detection. RPA development and platform management: UiPath (including AutoPilot), with automation governance and COE operations. Python fluency with modern AI/ML libraries (PyTorch, Hugging Face Transformers, LangChain). MCP (Model Context Protocol), tool-calling, and agent orchestration patterns; enterprise integration, API-based automation, and workflow orchestration. Preferred Qualifications Experience in semiconductor, advanced manufacturing, or capital equipment industries, with familiarity applying AI/ML to quality, supply chain, or engineering operations. Contributions to AI governance frameworks, responsible AI policies, or AI ethics programs at the enterprise level, plus recognized industry contributions (awards, publications, conference talks, open-source). Degree in Computer Science, Machine Learning, or a related technical field. Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 20% of the Time Relocation Eligible: No The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement. Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law. In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at View email address on click.appcast.io, or by calling our HR Direct Help Line at View phone number on click.appcast.io, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications. 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