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# Agentic AI Software Engineer - Equipment Data Analytics

- **Company:** KLA-Tencor
- **Location:** Milpitas, CA, United States
- **Experience:** Expert
- **Salary:** $136,300.0 - $199,900.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Big Data, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Software Quality, Computer Programming, Databases, Computer Engineering, Continuous Integration, Data Systems, Decision-Making Software, Graph Database, Python (Programming Language), Knowledge Management, NoSQL, Operational Data Store, Object-Oriented Software Development, Reliability Engineering, Software Engineering, Software Systems, SQL Databases, Data Streaming, Web Applications, ReactJS, Large Language Models, Multi-Agent Systems, Software Application Programming, Generative AI, Backend, Agentic-AI, Event Driven Architecture, Information Technology, Data Analytics, Data Management, Machine Learning Operations, Invoking Functions, Software Version Control, Data Pipelines
- **Published:** October 8, 2026
- **Apply:** https://kla.wd1.myworkdayjobs.com/Search/job/Milpitas-CA/Agentic-AI-Software-Engineer---Equipment-Data-Analytics_2641710

## About the Role

* 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., * 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., Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

## Description

* 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.