Role Overview
Databricks is hiring a entry-level AI Operations. This is a full-time role in United States. posted today. applications are still in the early window, before most candidates have applied. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job description
SLSQ327R184
Product Manager, AI Ops
We are reimagining GTM at Databricks and are seeking a hands-on, technical Product Manager to own AI-powered GTM agents end-to-end - building and prototyping agents directly on Databricks. You'll sit on the AI Ops team, between senior GTM leadership, Sales Ops, and the field - translating field reality into a product roadmap that improves how Databricks sells at every stage of the motion.
This is a hands-on IC engineering role for someone who understands how AEs, BDRs, and CSMs actually operate and wants to build the agents that reimagine GTM processes in the age of AI.
Key Responsibilities
- Build agents on Databricks (the core of the role): Design, prototype, and ship GTM agents yourself on the Databricks platform. Write the workflow logic and tools, stand up and iterate on agents in notebooks and SQL, and debug and validate behavior with your own queries. This is hands-on building, not spec-and-handoff.
- Agent behavior and quality: Define and implement how agents behave: decision logic, escalation paths, governance guardrails, and edge-case handling. Build evaluation in from the start: run experiments and A/B tests, measure quality, and tune prompts and workflows based on what the results show.
- Own your agent surface end-to-end: Set the 2-quarter roadmap for your agent area, make the prioritization calls, and write the lightweight specs (PRDs / Business Intent Docs) that frame what you build. Advocate for regional and segment specific needs as team roadmaps come together.
- Voice of the field: Run structured feedback loops with end users (often AEs and front-line managers) and convert what you hear directly into agent improvements you build and ship yourself rather than handing off a backlog.
What We Look For: The two things that matter most: you can build on Databricks yourself, and you have a strong gut for product development, UI, and the seller experience.
- Hands-on technical builder for the AI-stack: You build on Databricks. You're comfortable in notebooks and SQL, can stand up and iterate on agents and workflows on the platform yourself, read and debug an AI workflow, and write a query to validate behavior. This is a build role, not a spec-and-handoff role.
- Strong understanding of the seller experience: You have a sharp gut for product development and UI, and you can tell when an agent helps a seller vs. gets in the way and creates more overhead. You can sit with an AE for an hour and walk away with a prioritized list of where to build, and you can feel out the difference between a personal preference and a best practice worth replicating.
- Pattern recognition & judgement: You take field feedback seriously even when the data disagrees, and you know the difference between a one-off complaint and a signal worth a roadmap slot.
- Bias to ship: The roadmap moves fast and you'll own rollout gates, balancing speed against quality.
- Experience: 5+ years in product management, GTM strategy, sales ops, or a field-adjacent role such as Solutions Architect, with at least 3 years owning a product or program end-to-end. A strong, firsthand understanding of the AE workflow and how reps actually sell matters more than the title on your resume. Hands-on experience building on Databricks (SQL, notebooks, and agent or workflow tooling) or similar technology stacks is a strong plus.
Why This Role
This is one of the top FY27 GTM bets at Databricks and the MVP is in production globally with 1,200+ sellers. You will have an outsized impact on how Databricks sells in FY27. If you want to build and innovate at the bleeding edge of what's possible with AI and system automation, and do it inside a mature, high-velocity business with real stakes, this is the role for you.
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.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.
About Databricks

Databricks
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Frequently Asked Questions
How do I apply for the AI Operations position at Databricks?
Use the Apply button above to submit your application directly to Databricks. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the AI Operations position at Databricks located?
This position is based in United States. Databricks has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a AI Operations at Databricks earn?
Databricks has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the AI Operations role at Databricks posted?
This role was posted on July 22, 2026 (today). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
Is the AI Operations role at Databricks entry-level?
Yes. This is an entry-level position. Strong candidates typically have 0-2 years of relevant work experience, internships, or significant project work. Read the full description for any specific qualification requirements Databricks has listed.
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