Staff Backend Software Engineer- (AI Platform)

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