Top Remote Senior Level QA Engineer Jobs in Washington DC,

The Senior AI Engineer will design and develop AI models, build data pipelines, implement machine learning algorithms, and integrate AI applications while collaborating with cross-functional teams to solve complex business problems and enhance the platform's AI strategy.

The Frontend Developer will lead the development of the front-end user interface for Shift4’s ERP, collaborating with backend teams and focusing on automation, testing, and documentation. There is an emphasis on continuous improvement and creating a seamless user experience across a global workforce.

As a Senior Back-end/Full Stack Developer, you will design, develop, and maintain web applications focusing on user experience. You will collaborate with cross-functional teams, optimize databases, write unit tests, and stay updated with industry trends while resolving complex technical issues.

The Salesforce Developer will optimize commercial team systems focusing on Salesforce and third-party applications. Responsibilities include project management, designing custom solutions, collaborating with stakeholders, performing testing, and providing user training. The role requires strong Salesforce development and configuration skills to enhance system functionality and support business processes.

The Senior Software Engineer will be responsible for designing, building, testing, deploying, and maintaining full stack and mobile applications, primarily using technologies like React and Python. Collaboration with product managers and designers is key, as well as improving team processes and participating in code reviews.

The Platform Engineer will manage end-user technology, ensuring stability, security, and performance across systems. Responsibilities include overseeing software deployment, patch management, and operating system maintenance to enhance user experience and operational efficiency.

The Cloud (AWS) / Databricks Technical Architect will lead the design and implementation of cloud-based data architectures, utilizing AWS services and Databricks environments for analytics and machine learning. Responsibilities include developing data pipelines, ensuring security compliance, and optimizing data lakes and warehouses.