Top Senior Level DevOps Jobs in Washington DC,

Lead the architecture and development of a next-generation data and reporting platform. Collaborate with stakeholders to understand data needs, design ETL processes, create data models, and optimize data visualization solutions. Ensure security compliance and maintain platform performance while adhering to agile methodologies.

As a Senior Software Engineer at Terraformation, you'll be responsible for enhancing existing applications, contributing to backend development, participating in code reviews, and collaborating across teams to optimize processes and systems. You'll also engage in the hiring process and support incident responses for service quality.

The Senior Software Engineer will design and develop scalable backend services for cloud infrastructure while collaborating with cross-functional teams. Responsibilities include maintaining system performance, responding to incidents, and participating in code reviews to enhance system reliability.

The Senior Software Engineer is responsible for designing and developing enterprise web and mobile applications, ensuring high performance and reliability. They will work in an agile environment, collaborating with teams to troubleshoot issues and enhance user experiences, while taking ownership of development tasks and leading initiatives for application improvements.

The Senior Software Engineer will work on the VergeSense Occupancy Intelligence Platform, driving customer-facing features and collaborating with various teams. Responsibilities include leading projects, developing APIs, managing data systems, and mentoring junior engineers.

The Senior Backend Engineer will join Backstage's web team to enhance and maintain backend systems, drive user-focused initiatives, and support creative projects in the entertainment industry. The role emphasizes collaboration, continuous improvement, and adopting advanced technology to enable diverse hiring practices.

The Senior Software Engineer will design and maintain ML infrastructures using Kubernetes, optimize ML inference with CUDA, and enhance CI/CD processes. The role involves leading model scheduling and resource allocation efforts while collaborating with teams to innovate ML deployment systems.