Senior Director, Enterprise AI & Automation

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.

## Qualifications

### Education:

Master's Degree

### Skills

Agentic AI, AI Governance, Data Modeling, LLM Architecture, Machine Learning (ML), Microsoft Azure AI foundry, Microsoft Power Automate Robotic Process Automation (RPA) (Inactive), Python (Programming Language)

### Certifications:

### Languages:

### Years of Experience:

15+ Years

### Work Experience:

## Additional Information

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### Shift:

10-Day 8-Hr (United States of America)

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### Travel:

Yes, 20% of the Time

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### Relocation Eligible:

No

### Referral Payment Plan:

Employee Referral (Standard)

Salary Range:

$224,000.00 - $308,000.00

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 committed to diversity in the workplace. All 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.