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# Senior Software Engineer - Backend

- **Company:** Databricks
- **Location:** Bellevue, WA, United States
- **Experience:** Expert
- **Salary:** $157,700.0 - $213,800.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Big Data, C++ (Programming Language), Software as a Service, Cloud Computing, Distributed Systems, Design of User Interfaces, Human-Computer Interaction, Machine Learning, Scala (Programming Language), Service-Oriented Architecture, Software Engineering, Systems Integration, Virtual Machines, Google Cloud, Cloud Platform System, Computer Network Technologies, Generative AI, Backend, Kubernetes, Information Technology, Build Tools, Serverless Computing, Databricks, Golang
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-backend-bellevue-wa--896f1b48-8b35-40c7-93b5-0b81c3e04672

## About the Role

Software Engineering, Artificial Intelligence (AI), User Interface/Experience (UI/UX), Virtual Machine (VM), Process Improvement, Software Engineering, Operating Systems, Team Player, Machine Learning, Cloud Computing, + BS (or higher) in Computer Science, or a related field

 + 5+ years of production level experience in one of: Java, Scala, Golang, C++, or similar language
 + Experience developing large-scale distributed systems
 + Experience working on a SaaS platform or with Service-Oriented Architectures
 + Experience with cloud technologies, e.g. AWS, Azure, GCP, or Kubernetes
 + Experience with security and systems that handle sensitive data

Pay Range Transparency

## Description

As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. Our backend teams span many domains, from OS/container systems, to serverless infrastructure, to partner integration, and to machine learning infrastructure.

Below are some example projects and the

 * Serverless platform: Build Databricks serverless platform that powers the big data, machine learning and Gen AI workloads. Automatically improve the performance and efficiency of workloads running on the platform while also ensuring they scale to millions of machines across a multi-cloud environment.
 * Core cloud platform: Build cutting-edge OS, container and networking technologies that power the entire Databricks infrastructure, from internal infrastructure, to serverful, and to serverless platform. Improve the security, efficiency and reliability across the fleet.
 * Partner ecosystem: Build and grow a partner ecosystem for Databricks SQL. Build and offer a variety of toolkits to support partners and customers' deep and seamless integrations with Databricks. Maintain and nurture productive and beneficial partnerships within the ecosystem.
 * Notebook dataplane: Build multi-language multi-user collaborative REPL experience for Databricks users with high level of reliability and responsiveness, with a focus on Data Science and AI/ML authoring and experimentation experiences in notebooks.
 * Application platform. Build tools, frameworks and platforms to allow Databricks engineers to build, deploy and operate services with "batteries included". Improve the scale, observability and safety of all Databricks services across different clouds while improving every engineer's developer experience.