Sr. Product Manager, Databricks AI
As the Sr. Product Manager for Databricks AI, you will be instrumental in defining the future direction and feature set of our flagship artificial intelligence offerings. This role requires a deep understanding of LLMs, GenAI workflows, and the modern data stack. Key responsibilities include gathering requirements from technical leaders, prioritizing complex backlogs, and translating cutting-edge research into scalable product features that empower enterprise adoption. You will collaborate closely with engineering and data science teams to ensure a seamless and high-value developer experience. Ideal candidates possess proven PM experience in complex B2B infrastructure or AI domains, possessing exceptional communication skills and the ability to navigate ambiguity while maintaining technical rigor. This role is pivotal in accelerating our market leadership in the AI data space.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
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2100
Fragensatz
150
Dauer
Permanent
Schwerpunkte
People Also Ask (FAQs)
What is the last date to apply for Sr. Product Manager, Databricks AI?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Sr. Product Manager, Databricks AI?
Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.
Is there negative marking in the Databricks test?
The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.
What is the passing marks for this test?
The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.
How can I prepare for the Sr. Product Manager, Databricks AI test?
Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Product Management, Artificial Intelligence, Machine Learning, Data Strategy.
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