Strategic Overview
Staff Backend Software Engineer- (Databricks AI) at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as 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.
The role is listed for San Francisco, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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…
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…
Key Responsibilities & Objectives
- 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
Required Qualifications & Candidate Blueprint
- 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
Preferred Qualifications
- 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
Salary & Benefits
Published compensation: $166,000 – $225,000 USD
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Staff level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly 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. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.