Manager, Data Scientist

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:

Austin,TXYou’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 Lead the architecture, design, and implementation of Agentic AI solutions and Multi-Agent Systems that solve complex business and manufacturing challenges through autonomous reasoning, planning, orchestration, and execution.

Drive the development of AI agents using modern frameworks (e.g., Lang Graph, Auto Gen, CrewAI, Semantic Kernel, OpenAI Agents, Azure AI Foundry) to enable decision intelligence, workflow automation, knowledge retrieval, and operational optimization.

Serve as a hands-on technical leader responsible for building scalable AI platforms, including agent orchestration, memory management, tool integration, Retrieval-Augmented Generation (RAG), knowledge graphs, ontologies, and enterprise AI architectures.

Lead the development of advanced AI capabilities, including reasoning agents, planning agents, orchestration agents, code-generation agents, analytics agents, and domain-specific copilots that improve business outcomes and operational efficiency.

Collaborate with business stakeholders, product teams, engineers, data scientists, and subject matter experts to identify high-value AI use cases and translate them into production-grade AI solutions.

Establish AI engineering best practices covering LLMOps, AI governance, evaluation frameworks, observability, security, safety, prompt engineering, context engineering, model optimization, and continuous improvement.

Architect and develop enterprise AI platforms leveraging Azure AI, Databricks, Python, vector databases, graph databases, cloud-native technologies, and modern machine learning frameworks.

Build and optimize agent memory architectures, semantic layers, knowledge repositories, and enterprise ontologies to improve reasoning quality, contextual awareness, and autonomous execution.

Lead proof-of-concept development, rapid prototyping, and production deployments while ensuring scalability, reliability, maintainability, and measurable business value.

Mentor and guide AI engineers and data scientists while remaining actively involved in coding, architecture reviews, solution design, model development, and technical problem solving.

Stay current with emerging advances in Generative AI, Agentic AI, foundation models, reasoning systems, and autonomous agents, driving adoption of innovative technologies across the organization.

Required Education Background Bachelors in one of the following Computer Science, Artificial Intelligence or…