Senior Software Engineer (Manufacturing Platform)

Responsibilities

• 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.

Qualifications

• 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.
• A 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.