Software Application Development Engineer

Intel Corporation•Hillsboro, OR

1d•$117,620 - $227,270•Hybrid

About The Position

As a Software Application Development Engineer, you will design, develop, test, and maintain front-end and back-end software solutions that enhance Intel's semiconductor manufacturing processes. The role supports factory automation and operational excellence by optimizing manufacturing systems that are critical to Intel's advanced semiconductor production. You will be part of Intel Foundry, a business group providing technology and solutions for semiconductor manufacturing. The team's work enables factory automation and data-driven insights to improve manufacturing processes and efficiency and support the delivery of world-class semiconductor products.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or a related STEM field.
4+ years of experience in software development and design, or 3+ years with a Master's degree, or 0 years with a PhD.
2+ years of experience with object-oriented programming languages, specifically C#/.NET or Python.
2+ years of experience with relational database technologies such as Oracle or SQL.

Nice To Haves

Hands-on experience with semiconductor manufacturing or factory automation systems, mission-critical products, and SPC.
Experience with modern development tools such as Visual Studio, GitHub, Jira, CoPilot, and CI/CD.
Experience with Agile methodologies and DevOps practices.
Experience with systems engineering concepts, including Windows, firewalls, and distributed environments.

Responsibilities

Design and develop software applications for factory automation systems, including Statistical Process Control (SPC).
Implement and test application and database software releases while adhering to secure coding practices.
Collaborate with customers and partners to gather requirements, analyze user stories, and design solutions for manufacturing challenges.
Perform unit, integration, and end-to-end testing to ensure high-quality software delivery.
Document technical processes and systems to support post-deployment troubleshooting and scalability.
Automate build and deployment processes using modern tools and methodologies.
Collaborate with cross-functional teams on data-driven solutions using machine learning, statistical analysis, and optimization algorithms.