Top QA Engineer Jobs in Tucson, AZ

The Integration System Engineer II is responsible for maintenance and configuration of integration endpoints for ERP systems, focusing on post implementation support and ensuring data accuracy. They troubleshoot connectivity issues, offer technical solutions, manage escalations, and collaborate with project teams and customers.

As a Senior Software Engineer at Place Exchange, you will develop scalable systems for an out-of-home digital ad exchange. Responsibilities include shipping features independently, mentoring junior developers, collaborating on technical strategy, and maintaining code quality through best practices. You will utilize technologies like Python, Django, and AWS to handle billions of transactions efficiently.

As a MuleSoft Developer, you will design and code functional APIs and applications, manage API integrations, and ensure effective deployment and configuration. You will also validate and test integrations and work closely with clients and team members to align API management with business needs.

As a Senior Salesforce Administrator, you will manage daily operations of Salesforce, optimize business processes, provide user support and training, develop new functionalities, ensure data integrity, integrate Salesforce with other applications, collaborate with teams, and maintain documentation.

The Test Engineer will conduct controlled and real-world testing of radar sensors, document observations, and collaborate with the hardware testing team to ensure efficient testing processes. The role involves gathering equipment, following outlined test plans, and communicating data storage locations for further analysis.

The Quality Engineer is responsible for quality assurance documentation, data analysis, and reporting to assess manufacturing progress and support data-driven decisions. The role involves investigating non-conformances, evaluating compliance with specifications, improving product quality, maintaining quality management systems, and conducting audits.

The role involves designing and implementing optimized communication libraries for Deep Learning systems, collaborating with hardware and software teams to ensure data synchronization across AI accelerators, and optimizing algorithms for distributed computing applications.