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Senior Backend Software Engineer- (AI Platform)

Databricks · Mountain View, California; San Francisco, California
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Full job post · as written by Databricks

P-1428

At Databricks, we are passionate about enabling data and AI 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 and AI infrastructure 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 solve 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.

As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI.

We’re hiring across multiple teams in our AI Engineering org including:

The impact you will have

  • Build infrastructure that powers our flagship offerings like MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few.
  • Improve reliability, latency, and efficiency of distributed AI workloads
  • Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences
  • Shape how developers and data scientists build and interact with AI on Databricks

What we look for

  • 5+ years of experience in backend or infrastructure engineering
  • Strong programming skills in Scala, Go, or Python
  • Experience with distributed systems, scalable APIs, or cloud-native infrastructure
  • Familiarity with service-oriented architecture, deployment pipelines, and system observability
  • Strong product and ownership mindset — you care about building the right solution, not just any solution

Bonus points for

  • Experience with real-time serving, ML infrastructure, or GPU orchestration
  • Exposure to platforms like SageMaker, Vertex AI, or Azure ML
  • Contributions to OSS projects like MLflow, PyTorch, or Ray
  • Built developer platforms or internal tools supporting AI workflows

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,…

Apply on Databricks's site ↗Opens Databricks's official careers page. Your application goes straight to them.
Company
Databricks
Location
Mountain View, California; San Francisco, California
Work mode
On-site
Level
Senior
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Apply on Databricks's site ↗Opens Databricks's official careers page. Your application goes straight to them.

Overview

You will build core infrastructure for Databricks’ AI platform, including model serving, agent frameworks, and MLflow, enabling scalable AI deployment for enterprise customers.

Skills

ScalaGoPythonDistributed systemsAPI designMLflowGPU orchestration

Responsibilities

  • Develop core infrastructure for model serving, AI agents, and MLflow
  • Improve reliability and latency of large-scale distributed AI workloads
  • Collaborate with ML and infra teams on end-to-end user experiences
  • Design scalable solutions for developer and data scientist AI workflows

Requirements

  • 5+ years of experience in backend or infrastructure engineering
  • Strong programming skills in Scala, Go, or Python
  • Experience with distributed systems and scalable API design
  • Familiarity with service-oriented architecture and system observability
Nice to have
  • Real-time serving or GPU orchestration experience
  • Experience with ML infrastructure platforms like SageMaker or Vertex AI
  • OSS contributions to MLflow, PyTorch, or Ray

About Databricks

Databricks provides a unified data and AI infrastructure platform for organizations to build, scale, and manage data and AI applications.

What to prepare

Distributed systems designAI infrastructureLatency optimization
Summarised by AI from the job post. Check the full post before applying.