Senior Director, AI Technical Programs

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:

$200,000.00 - $275,000.00

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. 

General Profile

This role leads the company’s AI work that directly helps the Process Support Engineer (PSE) community move faster and work more consistently. You’ll set direction, keep the program moving, and make sure we’re getting real results—better tools, better knowledge access, and better training—without creating risk around security, IP, or compliance. You’ll work across Field teams, Business Units, Digital/IT, compliance partners, and learning/training groups, and you’ll also lead a small team of AI practitioners who build and scale solutions.

A big part of the job is working with internal AI leadership teams and the BUs to adopt best practices, align roadmaps, and pull together multiple separately-built capabilities into a smaller set of solutions that are truly optimized for PSE workflows. And once something is ready, you make sure it actually lands in the field with hands-on, PSE-relevant training (not just a slide deck and a link).

Competencies

In plain terms, you’re great at:

• Running big technical programs end-to-end (scope, schedule, priorities, risks, budgets, and outcomes).
• Working with lots of stakeholders and keeping people aligned when priorities compete.
• Influencing without authority—especially across BUs and centralized AI groups.
• Thinking clearly with messy inputs and making good calls with incomplete information.
• Explaining technical topics simply—from leaders to working-level engineers.
• Building practical AI solutions (GenAI/AI for engineering workflows), plus knowing how to handle data governance, security, Responsible AI, and model lifecycle realities.
• Knowledge systems and retrieval—how to structure information so people (and AI) can actually find and use it.
• Enough PSE workflow and integration awareness to understand what will (and won’t) work in the field.

Key Responsibilities

What you’ll actually do:

Build AI that helps PSEs every day. Focus on high-frequency work like finding the right info fast, summarizing technical content, supporting troubleshooting, automating repeatable workflows, generating reports, and improving structured documentation. Use AI to build and maintain PSE knowledge bases. That includes making content “AI-ready,” keeping it updated, and putting the right controls around it so the right people can access the right information. Make knowledge easy to access. Deliver practical “chat/search/assistant” style access so PSEs can get answers faster, follow consistent guidance, and reuse validated best methods—without compromising classification, IP, or compliance. Evaluate tech—inside and outside the company. Look at platforms, models, tools, vendors, and services. Run pilots, compare options, and recommend what actually improves PSE capability and productivity. Own the roadmap and results. Define what success looks like, prioritize use cases, track progress, manage risks, and report outcomes in a way leaders can trust. Lead a small team of AI practitioners. Help them prototype, build, and harden solutions—then integrate them with real data sources and existing systems so they work in practice, not just in a demo. Show the work and listen hard. Run demos, evaluations, and beta programs with PSEs and leaders. Capture feedback and iterate until it’s truly useful and scalable. Train the PSE community to use AI well. Create hands-on training, playbooks, and working sessions that build practical skill and improve job velocity. Measure adoption and proficiency so we know what’s working. Translate real PSE pain into buildable requirements. Partner with Field and BU leaders to make sure the AI work connects to customer-impacting outcomes and not just “cool tech.” Align with AI leadership + converge BU capabilities into PSE-optimized solutions. Work with internal AI leadership teams and the BUs to adopt shared best practices and standards, influence convergence of separately developed AI capabilities into PSE-optimized solutions, and drive field rollout with hands-on, PSE-relevant training. Set guardrails and standards. Make sure prompts/workflows are high quality, outputs are validated where needed, and solutions are auditable and safe to use in quality/customer environments. When it makes sense, bring in outside help. Lead external acquisition of AI talent or technology so PSE AI capabilities stay current as the landscape changes.

Functional Knowledge

You understand AI/ML and GenAI well enough to turn ideas into solutions, and you also understand the “plumbing” that makes it real: knowledge systems, retrieval, data quality, governance, and the constraints of deploying AI in a global engineering environment. You can connect this to PSE value levers like cycle time reduction, consistent technical guidance, better reuse of learnings, and stronger escalation support.

Business Expertise

You can translate AI work into outcomes the business cares about—productivity, quality, and operational performance. You can build a clear value case, track impact, and balance benefits against cost, risk, and change effort across regions, customers, and product lines.

Leadership

You lead both directly (your team) and indirectly (through influence). You set clear goals, keep a steady operating rhythm, develop talent, and create a culture where people can experiment responsibly, learn fast, and ship improvements that stick.

You also build alignment with internal AI leadership teams and BU partners so we reuse what works, reduce duplicated effort, and accelerate adoption of proven solutions across the PSE community.

Problem Solving

You tackle complicated, messy problems by being systematic—breaking things down, testing assumptions, using data, and improving continuously. When an AI solution isn’t working, you know how to diagnose whether the issue is the data, the retrieval, the prompt/workflow design, the model behavior, or the system integration—and then fix it.

Impact

If you do this job well, PSEs ramp faster, find answers faster, reuse the best information more consistently, and spend less time reinventing work. The broader organization benefits too, because the AI capabilities and standards you build help other teams operate more efficiently and consistently.

Interpersonal Skills

You’re comfortable working with senior leaders and technical experts, and you can influence decisions without forcing them. You communicate clearly, adjust to the audience, and build trust—especially when the topic is sensitive (IP, security, compliance) or when teams have competing priorities.

Position requires understanding of Applied Materials global Standards of Business Conduct and compliance with these standards at all times, including demonstrating the highest level of ethical conduct reflecting Applied Materials’ core values.

Education and Experience

Education: Bachelor’s Degree (preferred: Master’s in CS, Data Science, Engineering, or related).
Experience: 10–15 years (preferred: leading cross-functional technical programs and delivering AI/ML or GenAI solutions from prototype through scaled deployment in an enterprise setting).

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 25% 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 Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, 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.