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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.
We are seeking a hands-on techno-functional specialist to drive AI-enabled improvements across CSP services—portfolio/demand management, execution governance (SDLC), tool adoption, compliance, and metrics/KPIs.
This specialist will design, build, and integrate AI features—such as predictive analytics, automated task assignment, and intelligent chatbots—into project management software to optimize workflows, mitigate risks, and boost overall team efficiency.
This is a hybrid, high-impact role requiring a professional who speaks both "business" and "code." You will act as a bridge between executive stakeholders, end-users, data scientists, and core development teams. Your primary mission is to translate complex business problems into actionable AI-enhanced technical architectures within enterprise project management systems (e.g., Jira, Asana, custom enterprise applications).
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Translate business requirements into technical specifications and system architectures for AI-driven project management capabilities.
Design and integrate Large Language Models (LLMs), machine learning models, and Agentic AI into existing project environments to automate scheduling, risk identification, and resource allocation.
Evaluate the technical feasibility of proposed AI features and recommend the optimal technology stack
Implement and deliver the approved solutions
Work with GIS Data team to ensure data availability, quality, and governance required to train accurate, domain-specific AI models
Lead the end-to-end execution of AI initiatives, maintaining sprint cycles, backlogs, and milestone tracking.
Act as the technical point of contact AI for assigned product family coordinating multidisciplinary teams of developers, data engineers, and domain experts.
Monitor system reliability, model observability, and overall performance metrics
Tool integration experience across documentation → backlog → execution → reporting flows.
Reporting/analytics experience for productivity, compliance, and operational insights.
Good to have Python, SQL and programming background.
Verified company details for this employer are not available yet.
Full-time
Senior · 10+ years experience
Hybrid
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