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:

$ - $

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 Auto Pilot) 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…