Top Entry Level DevOps Jobs in Kansas City, MO

GFiber seeks talented individuals for their Engineering & Technology Team, focused on providing excellent internet services. While no specific openings are listed, interested candidates are encouraged to submit their information for future opportunities in internet technology and engineering roles.

The Software Engineer on the Developer Platform team at Glydways will maintain and enhance developer workflows, collaborate on improvements to the CI system, develop automation tools, design monitoring services, and assist in migrating the build system to Bazel.

The AI Software Engineer will develop components of an AI software stack, optimize applications, implement mathematical operators, and validate models on new hardware platforms. The role requires collaboration and a strong desire to learn new skills.

The SAP BPC Backend Developer will be responsible for backend development, including BPC script logic and BADI implementation, ABAP programming, and SAP BW modeling and integration with BPC. The role requires strong knowledge of financial planning and analysis as well as developing data models within SAP BW. Candidates should have experience in customizing business rules and calculations for financial applications.

RocketReach is seeking a Senior Backend Engineer to join their Core Data team and work on critical customer-facing product features. Responsibilities include building data pipelines for machine learning models, designing algorithms to work at scale, and maintaining the data platform. The salary range for this role is $170,000 - $200,000 per year.

As an Associate Integration Engineer, you will develop integration patterns and plans for customer-centric solutions while collaborating with various teams. The role focuses on integrating Protegrity's products with enterprise data solutions, aiming to enhance customer experiences across multiple environments.

The Data Pipeline Solutions Engineer develops and deploys data solutions for customers, ensuring optimal performance of data pipelines. Responsibilities include customer development, troubleshooting pipeline issues, managing software testing processes, ensuring data quality, training neural networks, and improving deployment tooling.