Staff Product Manager, AI Platform
Databricks · Seattle, Washington · Product · listed February 18, 2026
The shape of it
Seniority
Manager
Experience asked
5+ years
Where
Not stated
Stated pay
$172,600 – $237,325 USD
Requirements listed
4
Length
970 words
In the posting’s own words
Our mission is to make it radically easier for enterprises to put AI into production. We do this by providing a unified, governed, and performant AI platform that integrates deeply with the Databricks Data Intelligence Platform — connecting MLflow, Unity Catalog, Model Serving, Vector Search, Feature Engineering, LLM, and Agent infrastructure into a cohesive experience. You will join a team that ships products used by thousands of the world's most sophisticated data and AI organizations.
What it asks for · 4
- 5+ years of experience as a Product Manager working on platform or infrastructure products, ideally in ML/AI, data, or cloud services.
- Deep technical background — CS, EE, or equivalent degree strongly preferred; former software engineer experience is a significant plus. You should be comfortable going deep on system architecture, writing technical specs, and engaging credibly with world-class ML engineers.
- Experience with ML/AI infrastructure, data platforms, or cloud services (e.g., model training, model serving, feature stores, vector search, LLM infrastructure, ML pipelines, or similar systems). Familiarity with recommendation systems is a bonus.
- Proven enterprise B2B product management experience with highly technical customers — you have shipped platform products, driven commercial outcomes, and worked with field teams to land enterprise deals.
What the job covers
- You will own the product roadmap for AI platform areas — defining what we build, why, and in what order — to accelerate customer adoption of AI and ML in production.
- You will drive strategy for key AI platform capabilities, shaping how enterprises operationalize AI at scale.
- You will partner closely with engineering teams to make deeply technical decisions about ML infrastructure — from distributed training architectures to real-time serving systems.
- You will represent the voice of the customer by engaging directly with enterprise ML teams, translating their pain points and workflows into platform capabilities that simplify the path to production AI.
- You will collaborate with GTM, Solutions Architecture, and Customer Success teams to drive enterprise adoption, shape field enablement, and inform competitive positioning.
- You will define pricing, packaging, and commercialization strategy for AI platform features, working with business teams to maximize value capture.
- You will grow end-user engagement with Databricks AI tools by identifying adoption bottlenecks and partnering cross-functionally to remove them.
Degree language
- Deep technical background — CS, EE, or equivalent degree strongly preferred; former software engineer experience is a significant plus. You should be comfortable going deep on system architecture, writing technical specs, and engaging credibly with world-class ML engineers.
Tools and skills named
Models & research
- Machine learning11×
- LLM3×
- Inference
Data
- Databricks5×
- Experimentation
Product & design
- Product management2×
- Roadmap2×
- User experience
Go to market
- Customer success
- Go-to-market
- Solutions architecture
Words the posting leans on
- platform13×
- data9×
- infrastructure9×
- product8×
- customer7×
- systems7×
- enterprise6×
- experience5×
- feature5×
- production5×
- technical5×
- build4×
- engineering4×
- training4×
- adoption3×
- architecture3×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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