Synced from Greenhouse · Oct 2

Sr. AI Operations Specialist — Sales Operations

DatabricksNew York; San Francisco, California; USCAPosted Oct 2, 2026
Business Operations ManagerMid
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$125k–$172k
Compensation
900
Other open Databricks roles
Oct 2
Posted
Greenhouse
Applicant system
Job descriptionReq 8821953002

SLSQ427R538

The impact you will have:

Databricks' Sales Operations team is transforming how operational work gets done. We are shifting from manual, high-volume request processing to an AI-first operating model — where AI agents handle repeatable work autonomously and the team focuses on building, governing, and improving those systems. This role is central to that transformation.

You will own a portfolio of AI agent workflows that automate business-critical Sales Operations processes. You translate business requirements into agent designs, deploy them into production, monitor performance, and continuously improve them. You also lead systems improvement projects — diagnosing integration issues, fixing data quality problems, and coordinating solutions across platforms.

This is a cross-functional role partnering with Strategy, Planning, Finance, IT, and Data Engineering teams across our enterprise systems stack.

  • Build and operate AI agents — translate operational SOPs into agent workflows; deploy, monitor, and fine tune agents that handle field requests autonomously
  • Own an agent portfolio — manage a set of automated workflows end-to-end, including agent-to-human escalation paths and performance optimization
  • Drive process and systems improvement — identify next workflows to automate; diagnose cross-system integration issues; lead data quality remediation
  • Partner cross-functionally — gather requirements from Sales, Finance, IT, and Strategy stakeholders; influence Directors and Sr. Directors on automation priorities
  • Support operational continuity — contribute to critical business processes including annual planning cycles

What we look for:

  • 5–8 years in operations, systems administration, or business process automation — ideally in high-growth tech companies
  • Systems fluency — understands APIs, data schemas, and integration patterns; knows how enterprise systems connect
  • AI-native thinking — uses LLMs, agent platforms, and automation tools to solve business problems; strong judgment on when to automate vs. when manual oversight is needed
  • AI agent deployment — hands-on experience building AI agents or automation workflows
  • Process design — thinks in systems, not tasks; proven track record designing and improving operational workflows
  • Cross-functional influence — comfortable gathering requirements across multiple teams and influencing Director-level stakeholders
  • Bias for action — self-motivated; finds ways forward with AI tools rather than waiting to be unblocked

 

 

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 base 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 anticipated 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.

 

Zone 1 Pay Range
$125,000—$171,950 USD
Zone 2 Pay Range
$112,600—$154,750 USD
Zone 3 Pay Range
$106,300—$146,200 USD
Zone 4 Pay Range
$100,000—$137,500 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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Sr. AI Operations Specialist — Sales Operations
Databricks · New York; San Francisco, California; USCA
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