✦ Luna Orbit — Software Engineering

Senior Backend Software Engineer- (AI Platform)

at Databricks

📍 Mountain View, California; San Francisco, California Unknown Posted March 10, 2026
Type Not Specified
Experience mid
Exp. Years 5+ years
Education Not specified
Category Software Engineering

This role involves developing backend infrastructure and distributed systems to support AI workloads, focusing on scalable, cloud-native solutions and ML platform integrations.

  • Build scalable backend systems
  • Enhance distributed system performance
  • Integrate ML infrastructure with cloud platforms
  • Develop real-time AI serving solutions
  • Contribute to open-source ML projects

The technical environment includes distributed systems, APIs, cloud-native infrastructure, ML infrastructure, GPU orchestration, and platforms like SageMaker, Vertex AI, and Azure ML, primarily supporting AI and ML workloads.

The ideal candidate is a senior backend engineer with 5+ years of experience in building distributed, cloud-native systems, and expertise in ML infrastructure, APIs, and real-time serving, with a strong product and ownership mindset.

Backend engineeringDistributed systemsAPIsCloud-native infrastructureSystem observability
Real-time servingML infrastructureGPU orchestrationPlatforms like SageMakerVertex AIAzure MLOpen-source contributions
MLflowSageMakerVertex AIAzure MLPyTorchRay
ScalaGoPythonDistributed systemsAPIsCloud-native infrastructureService-oriented architectureDeployment pipelinesSystem observabilityML infrastructureSageMakerVertex AIAzure MLPyTorchRay
ScalaGoPythonDistributed systemsAPIsCloud-native infrastructureService-oriented architectureDeployment pipelinesSystem observabilityReal-time servingGPU orchestrationML infrastructureSageMakerVertex AIAzure MLOSS projectsMLflowPyTorchRay
OwnershipCollaborationProblem-solvingProduct mindsetTechnical leadership
Industry SaaS
Job Function Developing scalable backend infrastructure for AI and ML workloads
ScalaGoPythonDistributed systemsAPIsCloud-native infrastructureService-oriented architectureDeployment pipelinesSystem observabilityML infrastructureGPU orchestrationReal-time servingMLflowPyTorchRaySageMakerVertex AIAzure ML

Less than 5 years of experience, Lack of experience with distributed systems or ML infrastructure, No knowledge of cloud platforms like SageMaker or Azure ML, Unwillingness to work on infrastructure at scale

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