Top Senior Level DevOps Jobs

The Azure Platform Lead/Architect at KYNITE is responsible for client management, supporting team operations, and managing Azure Cloud services. The role requires extensive experience in Azure, Linux, and Hadoop, along with team leadership and communication skills. The position is set in a dynamic, 24x7 support environment, emphasizing troubleshooting and resource management in cloud environments.

The Senior Automation Engineer will develop and optimize protocols for liquid handlers, implement automated workflows, troubleshoot lab automation systems, and collaborate with teams to enhance lab efficiency and capacity for gene editing therapies.

As a Sr. Engineering Manager at Hims & Hers, you will lead a team to develop and manage their EMR platform. Responsibilities include mentoring engineers, collaborating with product and program managers, and ensuring project delivery aligned with strategic goals. You will also manage technical risks and stay updated with industry trends.

The GIS Architect will lead the design, development, and maintenance of geospatial systems critical to a government agency's mission, providing technical leadership in GIS solutions and implementing CI/CD practices to streamline processes.

The Senior Solution Architect will lead customer engagements, providing technical guidance in cloud and networking solutions. Responsibilities include understanding customer challenges, executing proof of concept trials, conducting training sessions, and collaborating with cross-functional teams to ensure customer success.

As a Senior Software Engineer at Expanso, you will lead the development of Bacalhau, focusing on performance, reliability, and scalability while collaborating with a cross-functional team. You will ensure coding excellence, troubleshoot issues, and iterate based on community feedback in a dynamic, innovative environment.

The Senior Cloud Engineer will optimize GridMatrix's data pipeline and cloud infrastructure, manage customer deployments, architect solutions for cost and performance, and build machine learning and analytics pipelines while measuring feature impact.