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This advert was matched to Sr. Software Engineer, a job title Databricks, Inc. has itself sponsored.
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The role, as Databricks, Inc. describes it
P-78 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
The filesystem has emerged as the preferred runtime interface for agentic AI. AI agents use the filesystem for context, memory management, artifact (dashboard, code etc) authoring, version control, sandboxing, and interacting between systems and agents. It is the foundational layer to accelerate AI adoption
As a Senior Software Engineer on the Files team, you will innovate at the intersection of storage, performance, and distributed systems, directly shaping our filesystem strategy to power next-generation agentic workloads.
The Impact You’ll Have
- Design, build, and operate the the filesystem platform powering tens of thousands of data, AI and agentic workloads daily
- Push filesystem performance for the most demanding workloads — profiling and optimizing across the stack, from the API layer down to the Linux kernel
- Partner with teams across the platform to design and evolve next-generation compute and storage architectures
- Set the technical direction for how content is organized across Databricks, standardizing around filesystem primitives that apply to every product surface
What We’re Looking For
- Bachelor's degree (or higher) in Computer Science or a related field
- 5+ years of production-level experience in Java, Scala, C++, Go, Rust, or a similar language
- 3+ years of experience developing large-scale distributed systems
- 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.
- Experience with filesystems and FUSE
- Experience building object/blob storage (S3, Azure Blob Storage, GCS etc)
- Systems performance engineering across microservices, down to the Linux level
- Background in high-scale content, storage, or file-sync products
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .
Local Pay Range $166,000 — $225,000 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .
Benefits
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