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# Senior Software Engineer, Compute Infrastructure

- **Company:** Databricks
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $164,200.0 - $205,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, C++ (Programming Language), Distributed Systems, Python (Programming Language), Scala (Programming Language), Google Cloud, System Availability, Multi-Cloud, Build Management, Kubernetes, Low Latency, Api Gateway, Serverless Computing, Docker, Databricks
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b5a92efd8a8eb6f2

## About the Role

* 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language
 * 4+ years of experience developing large-scale distributed systems from scratch
 * Experience with Kubernetes, Docker, or MicroVM technologies (e.g., Firecracker) and a strong grasp of cloud provider internals (AWS/Azure/GCP).
 * You aren't just a user of tools; you understand how to build them from the ground up when existing solutions fail at our scale.

## Description

As an engineer on this team, you won't just manage infrastructure; you will build it as a product. You will tackle the hard problems of distributed systems: sub-second container/MicroVM startup times, multi-tenant security isolation, and building a unified orchestration layer that scales across AWS, Azure, and GCP., * Design and build the next generation of our Serverless platform, focusing on high availability, low latency, and scale-to-zero efficiency.

 * Build a single compute stack that supports heterogeneous workloads, including GPU instance qualification for AI training and stateful execution for Lakebase.
 * Solve Multi-Cloud Complexity: Develop platform-level abstractions that allow Databricks to run seamlessly across all major cloud providers.
 * Optimize everything from the API gateway down to the host-level networking and container orchestration.
 * Work alongside industry experts who have built world-class systems like Borg, Kubernetes, and Uber's infrastructure.


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