Sr. Software Engineer- Databricks AI
Databricks is hiring a Sr. Software Engineer- Databricks AI in Bengaluru, India. Level rates it ; you can apply on Databricks.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- Tools and skills the posting cites include MLflow, Scala and Java.
- Level classifies it as a senior role.
- Level lists 921 other open roles at Databricks.
- The role was posted within the past two weeks.
AI in this role
Senior software engineer to design and build backend systems and evaluation capabilities for MLOps and LLMOps platforms.
At Databricks, we are passionate about helping enterprises that build ML models and AI agents deliver high-quality AI to production fast. Founded by engineers, and customer obsessed, we leap at every opportunity to tackle technical challenges, from designing great developer experiences to building reliable systems at global scale. And we're only getting started.
Our team builds the MLOps and LLMOps platform that millions of AI developers and ML practitioners use to track model training experiments, manage model registry, observe and evaluate AI agents. We're the team behind MLflow, the most widely adopted open-source AI engineering platform with more than 30 million package downloads per month, and its managed service used by thousands of organizations globally. We're now expanding to Bengaluru, India, and building our first AI engineering team there from scratch to work on this platform.
As a Senior Software Engineer and a founding member of the Bengaluru team, you'll design and build the backend systems behind these products and take them from design through production. This is an excellent opportunity for a hands-on engineer who thrives in a fast-paced environment.
Check out our recent blog post: coSTAR: How we ship AI agents at Databricks fast, without breaking things
The impact you will have:
- Design and implement core services and APIs for the platform, ensuring scalability, reliability, and operational excellence.
- Build systems that ingest, store, and query traces, metrics, and artifacts from training runs and production agents.
- Develop evaluation and monitoring capabilities, such as LLM judges and quality metrics, that catch regressions before they reach production.
- Optimize the scalability and cost of the platform as usage grows across customers and cloud regions.
- Work with product, research, and customers on what we build next.
- Establish best practices for code quality, testing, and operational readiness, and mentor other engineers.
What we look for:
- BS (or higher) in Computer Science, or a related field.
- 5+ years of experience developing large-scale distributed systems, scaling infrastructure, or building platforms and developer tools for other teams.
- Strong foundation in algorithms, data structures, and system design.
- Strong experience with backend technical stacks such as Scala or Java.
- Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes.
- Engineering maturity in security, correctness, and operational excellence.
- Strong communication skills and ability to collaborate across teams.
- Experience with ML or LLM systems is a plus.
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.
How we rate this
Sr. Software Engineer- Databricks AI at Databricks rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where system design was part of your work. What did you do?
- Tell me about a project where mlops was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, ML Ops, Distributed Systems, System Design, and MLOps. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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