• Led quality assurance efforts for cloud-based software solutions, ensuring compliance with industry standards and regulations such as DSCSA

• Developed and maintained automated test scripts using Robot Framework, Python, and Selenium, reducing manual testing time by over 80%.

• Collaborated with development teams to identify defects early in the lifecycle, improving software reliability and reducing production issues.

• Worked extensively with MySQL, SSH, Docker, Jenkins, and AWS to manage test environments and execute tests in scalable, cloud-hosted systems.

• Championed the implementation of DSCSA regulations by driving QA processes and ensuring product compliance.

• Automated and streamlined QA processes, resulting in significant improvements in testing efficiency and consistency.

• Mentored and supported team members to adopt best practices in testing and automation, fostering a culture of quality and collaboration.

• Utilized management skills for the development and negotiation of contracts, software, and customer relations

• Served as Application Engineer for projects and as an engineering liaison between sales, development, and customers

• Planned and executed installations with FANUC/Kawasaki robots, cameras, and Inos software in the automotive industry

• Responsible for upgrades and maintenance of Inos Build-Verification and Gap & Flush Moving Line Solutions

• Created VBA scripts for constructing weekly performance reports and delivered them to customers via teleconferences

• Developed MySQL scripts to streamline data analysis for customers and troubleshooting in the field

• Functioned in a project-management role for a 32-camera, 6 network switch Build-Verification system in Mississippi

• Trained customers and in-house personnel on Inos software to perform independently strengthening customer relations

• Implemented IP network subnets, ODBC, network mapping, grant privileges, and Python integration during projects

• Balanced camera focal length, apertures, exposure, and angle to achieve ideal images for verifying final production units