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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.
Skills Required
- Bachelor’s degree 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
- Strong foundation in algorithms, data structures, and system design
- Strong experience with backend technologies such as Scala or Java
- Experience with cloud technologies such as AWS, Azure, or GCP
- Experience with Docker and Kubernetes
- Engineering maturity in security, correctness, and operational excellence
- Strong communication and cross-functional collaboration skills
- Experience with ML or LLM systems
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
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Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
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Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
