Design, develop, and maintain the Python-based manufacturing platform that powers automated test across engineering builds and high-volume production.
Architect scalable software frameworks and services that integrate with automated test equipment, embedded devices, manufacturing systems, and cloud infrastructure.
Develop and maintain cloud-based services and infrastructure in AWS to support manufacturing applications, test execution, data collection, and operational monitoring.
Build and maintain internal APIs, tooling, and developer workflows that improve the reliability, maintainability, and usability of the manufacturing software ecosystem.
Partner closely with Manufacturing, Hardware, Firmware, Electrical, and Quality Engineering teams to translate manufacturing requirements into robust software solutions.
Drive engineering best practices through software architecture, automated testing, code reviews, documentation, and technical mentorship while continuously improving platform reliability and developer productivity.
5+ years of professional software engineering experience building production-quality applications and platforms.
Excellent Python development and debugging skills, with experience designing modular, maintainable software architectures.
Experience administering Linux systems and working comfortably in Windows development and production environments.
Experience designing and consuming RESTful Web APIs and building distributed software systems.
Hands-on experience developing, deploying, and administering applications and infrastructure within AWS.
Strong understanding of modern software development practices, including Git/GitHub workflows, software build systems, CI/CD, automated testing, and code review.
Experience integrating software with hardware, embedded systems, instrumentation, or automated test equipment is highly preferred.
Excellent communication skills and the ability to collaborate effectively across multidisciplinary engineering teams.
A strong commitment to leveraging AI tools to accelerate development, while maintaining rigorous quality standards and ensuring all AI-assisted output meets the same high bar as manual contributions.
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