Staff Backend Software Engineer- (AI Platform)

About the Role

Staff Backend Software Engineer- (AI Platform) - Databricks Skip to main content Login Why Databricks Discover For Executives For Startups Lakehouse Architecture Databricks AI Research Customers Customer Stories Partners Partner Overview Explore the Databricks partner ecosystem Partner Spotlight Featured partner announcements Partner Program Explore benefits, tiers and how to become a partner Cloud Providers Databricks on AWS, Azure and GCP Find a Partner Discover Databricks partners for your needs Partner Solutions Find custom industry and migration solutions Product Databricks Platform Platform Overview A unified platform for data, analytics and AI Data Management Data reliability, security and performance Sharing An open, secure, zero-copy sharing for all data Data Warehousing Serverless data warehouse for SQL analytics Governance Unified governance for all data, analytics and AI assets Data Engineering ETL and orchestration for batch and streaming data Artificial Intelligence Build and deploy ML and GenAI applications Data Science Collaborative data science at scale Business Intelligence Intelligent analytics for real-world data Application Development Quickly build secure data and AI apps Database Postgres for data apps and AI agents Security Open agentic SIEM built for the AI era Integrations and Data Marketplace Open marketplace for data, analytics and AI IDE Integrations Build on the Lakehouse in your favorite IDE Partner Connect Discover and integrate with the Databricks ecosystem Pricing Databricks Pricing Explore product pricing, DBUs and more Cost Calculator Estimate your compute costs on any cloud Open Source Open Source Technologies Learn more about the innovations behind the platform Solutions Databricks for Industries Communications Media and Entertainment Financial Services Public Sector Healthcare & Life Sciences Retail Manufacturing See All Industries Cross Industry Solutions AI Agents Cybersecurity Marketing Migration & Deployment Data Migration Professional Services Solution Accelerators Explore Accelerators Move faster toward outcomes that matter Resources Learning Training Discover curriculum tailored to your needs Databricks Academy Sign in to the Databricks learning platform Certification Gain recognition and differentiation Free Edition Learn professional Data and AI tools for free University Alliance Want to teach Databricks? 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Register Login Try Databricks Overview Culture Benefits Diversity Engineering Research Students & new grads Back to search results Staff Backend Software Engineer- (AI Platform) San Francisco, California Apply now 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 and AI infrastructure platform so our customers can use deep data insights to improve their business. Databricks’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency. As a Senior Engineer, you’ll play a critical role in shaping both the product experience and the foundational infrastructure of Model Serving. You will design and build systems that enable high-throughput, low-latency inference across CPU and GPU workloads, influence architectural direction, and collaborate closely across platform, product, infrastructure, and research teams to deliver a world-class serving platform. The impact you will have: Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence. Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads. Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale. Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems. Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers. Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance. What we look for: 5+ years of experience building and operating large-scale distributed systems. Experience in model serving, inference systems, or related infrastructure (e.g., routing, scheduling, autoscaling, and observability). Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems. Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value. Experience building architecture for large-scale, performance-sensitive CPU/GPU inference systems. Strong communication skills and ability to collaborate across teams in fast-moving environments. Customer-focused mindset with the ability to align implementation details with product goals. Passion for mentoring, growing engineers, and fostering technical excellence. 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 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter , LinkedIn and Facebook . 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, please visit https://www.mybenefitsnow.com/databricks . 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. 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