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cloud llms rag retrieval relevance📋 Description
- Work directly with enterprise customers, sales teams, and solution architects to understand requirements, negotiate priorities, clarify product needs
- Build, socialize and align a roadmap for core context engineering capabilities built on top of Elastic powered retrieval and relevance for AI Agents
- Deeply understand the AI Agent market, major players, trends and how it may impact our strategy
- Work directly data science and engineering to build out the strategy for benchmarking and evaluations of agent capabilities
- Work with design to build user experiences that address gaps in how agents show and refine context as they work
- Be the product expert and evangelize capabilities for Agent Builder through content like blog posts and open source projects
🎯 Requirements
- Extensive PM experience: 10+ years in technical/cloud/platform products
- AI/ML fluency: LLMs, RAG, vector databases, context engineering
- Bias to action: move fast and learn from experiments
- Leadership: lead across matrixed orgs and drive execution
- Communication: distill engineering details for diverse audiences
- Customer obsession: solve real customer problems for developers
Compensation for this role is in the form of base salary.
The typical starting salary range for new hires in this role is listed below.
The typical starting salary range for this role is:
$159,800—$252,800 USD
The typical starting salary range for this role in the select locations listed above is:
$191,900—$303,500 USD
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