Agentic AI Software Engineer - Equipment Data Analytics

KLA•Milpitas, CA

1d•$136,300 - $199,900•Onsite

About The Position

KLA is seeking an experienced Software Engineer to help build the next generation of AI-driven analytics and automation solutions for advanced semiconductor manufacturing systems. In this role, you will develop intelligent software platforms that combine large-scale equipment data, hardware telemetry, machine diagnostics, and Agentic AI technologies to improve equipment performance, reliability, and productivity. Working at the intersection of software, AI, big data, and complex hardware systems, you will build scalable applications that enable semiconductor engineers to diagnose issues, predict failures, and interact with sophisticated electron-beam inspection and metrology tools using natural language. This is a hands-on engineering role with global impact. The solutions you develop will be deployed within semiconductor manufacturing facilities worldwide, supporting some of the most advanced hardware systems used in semiconductor production.

Requirements

BS or MS in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical field.
5+ years of professional software engineering experience developing production applications.
Strong programming skills in Python and at least one object-oriented language such as Java, C++, or C#.
Experience developing scalable backend services, APIs, databases, and distributed software systems.
Experience working with hardware-integrated software systems, industrial equipment, manufacturing systems, instrumentation, embedded interfaces, controls software, telemetry systems, or IoT platforms.
Experience building data-intensive applications using SQL, NoSQL, streaming platforms, or large-scale data processing technologies.
Familiarity with cloud-native development, CI/CD pipelines, source control, automated testing, and modern software engineering practices.
Strong analytical and troubleshooting skills with the ability to work across multidisciplinary engineering teams.

Nice To Haves

Experience with semiconductor equipment, manufacturing systems, inspection systems, industrial automation, robotics, or scientific instrumentation.
Experience developing applications utilizing LLMs, Agentic AI frameworks, retrieval-augmented generation (RAG), tool/function calling, or AI orchestration frameworks.
Experience with vector databases, knowledge graphs, machine learning pipelines, or predictive analytics solutions.
Experience developing React-based user interfaces or modern web applications.
Understanding of equipment diagnostics, predictive maintenance, reliability engineering, or operational analytics.
Experience deploying software in secure, disconnected, or air-gapped environments.

Responsibilities

Design and develop production-quality software solutions supporting AI-driven equipment diagnostics, monitoring, and predictive maintenance.
Build and enhance Agentic AI frameworks that integrate large language models (LLMs) with engineering and equipment data systems.
Develop software that interfaces with complex hardware platforms, equipment telemetry streams, machine control systems, and manufacturing data sources.
Integrate AI technologies with scalable data platforms, including streaming architectures, NoSQL databases, vector databases, and knowledge management systems.
Build secure APIs, services, and orchestration layers that support intelligent workflows and automated decision-making.
Develop high-performance data pipelines that transform equipment and operational data into actionable insights.
Create intuitive user experiences and modern web applications that simplify troubleshooting and equipment diagnostics.
Collaborate across software, systems, hardware, data science, and product engineering teams to deliver end-to-end solutions.
Deploy and support solutions operating in highly secure, customer-controlled semiconductor manufacturing environments.
Drive software design, code quality, testing, and continuous improvement initiatives across the platform.