Job description

P-1591 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 $165,300 — $219,675 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 At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Requirements

Must-haves

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
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
Our Commitment to Diversity and Inclusion

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: greenhouse
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