Top DevOps Jobs

As a Senior Software Engineer, you will design and develop natural language understanding systems, utilizing your expertise in scalable web application architecture. You'll manage tasks from definition to deployment, collaborate with your team, and leverage your experience with AWS to ensure security and scalability of the applications.

The Principal Architect, Data Solutions at Zencore will collaborate with clients to understand their technical challenges, develop cloud technology solutions, lead project teams, and mentor engineers, ensuring end-to-end project delivery and strategic guidance.

The Salesforce Technical Architect will design and implement solutions on the Salesforce platform for nonprofit clients, lead technical design efforts, provide guidance to the development team, and assist with data migration. The role requires collaboration with various stakeholders to achieve optimal business outcomes.

As a Staff Software Engineer, UI, you will develop and maintain front-end architecture, collaborate with cross-functional teams to create user-friendly interfaces, optimize UI components for performance, and document coding best practices. You'll also refactor frontend components and work on the strategy for SEO and analytics.

The Senior Software Engineer at APrime will lead initiatives to enhance engineering productivity through platform improvements, collaborate on cloud infrastructure projects, develop maintainable code, and architect cloud-based solutions with minimal guidance.

As a Software Engineer III, you will design and implement algorithms for point-of-care diagnostic systems, ensuring adherence to medical device standards. You will work collaboratively with cross-functional teams, participate in troubleshooting, code reviews, and documentation while fostering a proactive and adaptive team culture.

The Software Engineer role focuses on developing and maintaining data ingestion and processing systems. Responsibilities include building cloud pipelines for data and image processing, managing data systems, and improving reliability as well as optimizing costs to scale AI detection capabilities.