Job description

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: $148,000.00 - $203,500.00 Location: Austin,TX 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 . Key Responsibilities • Own the product lifecycle for Agentic AI initiatives from ideation through deployment and value realization. • Partner with business stakeholders across engineering, manufacturing, supply chain, service, and corporate functions to identify opportunities for AI-driven workflow transformation. • Gather requirements, facilitate workshops, document business processes, and translate business challenges into product roadmaps, user stories, and implementation plans. • Lead cross-functional teams across the United States, India, and Singapore to deliver AI-enabled products on schedule and within budget. • Drive prioritization of product backlogs, roadmap decisions, release planning, and stakeholder communication. • Define success metrics, business KPIs, adoption goals, and ROI targets for AI initiatives. • Work closely with architecture and engineering teams to ensure solutions are scalable, secure, governed, and aligned with enterprise standards. • Develop executive presentations, strategy decks, architecture reviews, and steering committee updates that effectively communicate business value, progress, and risks. • Lead product demonstrations, stakeholder reviews, and adoption planning activities. Technical & Functional Knowledge The successful candidate should possess strong knowledge of modern Agentic AI architectures and understand how enterprise AI solutions are built, integrated, and deployed. Understanding of Agentic AI Architecture Ability to understand and discuss: • AI Agents and Multi-Agent Systems • Large Language Models (LLMs) • Retrieval Augmented Generation (RAG) • Agent Orchestration Frameworks • Semantic Layers and Enterprise Knowledge Systems • Agent Memory and Context Management • Human-in-the-Loop Workflows • AI Governance, Security, and Responsible AI • Observability, Monitoring, and Evaluation of AI Systems Enterprise Integration & APIs Strong understanding of how AI agents interact with enterprise systems through: • REST APIs and Application Integrations • ERP, CRM, MES, PLM, Service, and Manufacturing systems • Enterprise Data Platforms and Knowledge Repositories • Event-Driven Architectures and Workflow Automation Platforms • Authentication, Authorization, and API Security Concepts Model Context Protocol (MCP) Working knowledge of the Model Context Protocol (MCP) and related frameworks, including: • How MCP enables LLMs and AI agents to securely access external tools, applications, and enterprise data sources • Managing tool integrations and agent capabilities through standardized interfaces • Understanding of agent-to-tool communication patterns • Experience defining business requirements for MCP-enabled ecosystems that connect enterprise applications, workflows, and AI agents • Ability to partner with architects and engineers to identify use cases where MCP can accelerate integration and agent effectiveness AI Platform Awareness Familiarity with modern AI ecosystems such as: • Databricks • Lang Graph • Semantic Layers • Vector Databases and Enterprise Search Platforms Business Expertise • Understands how AI can improve operational efficiency, productivity, quality, and business decision-making. • Identifies high-value opportunities for workflow automation and intelligent process orchestration. • Develops business cases and value realization strategies for AI investments. • Anticipates organizational, process, governance, and adoption challenges associated with enterprise AI deployments. Leadership • Leads cross-functional product teams consisting of business stakeholders, architects, AI engineers, data engineers, and data scientists. • Influences decision-making across technical and business organizations. • Drives collaboration between global teams located in the United States, India, and Singapore. • Establishes governance, operating models, and stakeholder engagement frameworks for AI product delivery. Communication & Presentation Skills • Exceptional PowerPoint and executive communication skills. • Ability to create compelling presentations that clearly communicate business value, product strategy, roadmap, architecture, risks, and ROI. • Strong visual storytelling skills, including process flows, architecture diagrams, operating models, product roadmaps, and executive dashboards. • Comfortable presenting to senior leadership, steering committees, technical teams, and business stakeholders. • Ability to simplify complex Agentic AI concepts into clear, actionable business narratives. Preferred Qualifications • Experience managing AI, GenAI, Digital Transformation, Process Automation, or Agentic AI products. • Experience working with globally distributed teams and offshore development organizations. • Strong understanding of enterprise applications, APIs, workflow automation, and AI integration patterns. • Experience working with AI platforms, copilots, agent frameworks, and intelligent automation solutions. • MBA, Engineering, Computer Science, Information Systems, Analytics, or related degree preferred. Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 20% of the Time Relocation Eligible: Yes 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.

Requirements

Must-haves

Own the product lifecycle for Agentic AI initiatives from ideation through deployment and value realization.
Partner with business stakeholders across engineering, manufacturing, supply chain, service, and corporate functions to identify opportunities for AI-driven workflow transformation.
Gather requirements, facilitate workshops, document business processes, and translate business challenges into product roadmaps, user stories, and implementation plans.
Lead cross-functional teams across the United States, India, and Singapore to deliver AI-enabled products on schedule and within budget.
Drive prioritization of product backlogs, roadmap decisions, release planning, and stakeholder communication.
Define success metrics, business KPIs, adoption goals, and ROI targets for AI initiatives.
Work closely with architecture and engineering teams to ensure solutions are scalable, secure, governed, and aligned with enterprise standards.
Develop executive presentations, strategy decks, architecture reviews, and steering committee updates that effectively communicate business value, progress, and risks.
Lead product demonstrations, stakeholder reviews, and adoption planning activities.
Technical & Functional Knowledge
The successful candidate should possess strong knowledge of modern Agentic AI architectures and understand how enterprise AI solutions are built, integrated, and deployed.
Understanding of Agentic AI Architecture
AI Agents and Multi-Agent Systems
Large Language Models (LLMs)
Retrieval Augmented Generation (RAG)
Agent Orchestration Frameworks
Semantic Layers and Enterprise Knowledge Systems
Agent Memory and Context Management

Nice-to-haves

Experience managing AI, GenAI, Digital Transformation, Process Automation, or Agentic AI products.
Experience working with globally distributed teams and offshore development organizations.
Strong understanding of enterprise applications, APIs, workflow automation, and AI integration patterns.
Experience working with AI platforms, copilots, agent frameworks, and intelligent automation solutions.
MBA, Engineering, Computer Science, Information Systems, Analytics, or related degree preferred.
Additional Information

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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