Synced from Greenhouse · Sep 24

Software Engineer

DatabricksNew York City, New YorkPosted Sep 24, 2026
Software EngineerStaff
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$200k–$265k
Compensation
887
Other open Databricks roles
Sep 24
Posted
Greenhouse
Applicant system
Job descriptionReq 8842963002

Staff Software Engineer - Agent Quality

P-1567

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization is pushing the frontier of next-generation enterprise AI. We believe a company's data is its greatest competitive advantage, and we're building the models and agents that unlock it. Our work spans the full stack, from model training to advanced multi-agent systems. 

As a Staff Software Engineer - Agent Quality, you will be a founding member of a new team focused on evaluating and continuously improving Databricks' AI Agents. You will design and scale the infrastructure, tooling, and developer workflows that let researchers and engineers evaluate agents rigorously — driving a flywheel where evaluation results feed directly back into agent improvement across the full lifecycle, from development and training to production.

The impact you will have

  • Stand up the foundational evaluation infrastructure for Genie Agents, enabling rigorous benchmarking, regression detection, and quality measurement across research and product teams.
  • Build the flywheel that connects evaluation results back into agent improvement — closing the loop between production signals, training, and iterative development.
  • Shape the long-term technical direction for agent quality infrastructure, with real influence over how Databricks measures and improves its first-party agents and agent development platform.
  • Help shape the long-term technical direction for agent quality infrastructure as Databricks expands its first-party agents and agent development platform.

What we look for

  • 6+ years industry experience building software systems
  • Strong Python programming skills, with experience building production or research infrastructure
  • Experience building or operating distributed systems, data pipelines, or large-scale infrastructure with a focus on reliability, correctness, and operational maturity
  • Ability to design pragmatic but rigorous systems that produce trustworthy, reproducible signals for complex applications
  • Comfort working across ambiguous research and product boundaries, and partnering with both researchers and engineers to turn ideas into robust internal platforms
  • A high bar for technical quality, strong ownership, and the ability to influence roadmap and execution across multiple teams

Nice to have

  • Experience with devtools, CI/CD platforms, testing frameworks, observability tooling, or benchmarking infrastructure
  • Familiarity with how LLM or agent quality is measured — whether through evals, experimentation platforms, or production monitoring

 

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
$200,000—$265,000 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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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