Related skills
llms rag vector databases context engineeringπ Description
- Engage with enterprise customers, sales, and solution architects to define needs.
- Roadmap context engineering on Elastic retrieval/relevance for AI Agents.
- Understand AI Agent market, key players, trends, and impact on strategy.
- Work with data science/engineering to benchmark and evaluate agent capabilities.
- Partner with design to improve UX for agents showing and refining context.
- Evangelize Agent Builder via blog posts and open source projects.
π― Requirements
- 10+ years in product management or solution delivery for tech/cloud/platform products.
- AI/ML fluency: LLMs, RAG, vector databases, context engineering.
- Bias to action: move fast, learn from experiments; use AI tools to accelerate decisions.
- Leadership across a matrix org; drive execution in remote-first env.
- Excellent written and spoken communication; distill tech for execs and teams.
- Customer obsession: focus on developer needs and real-world problems.
π Benefits
- Competitive pay based on work, not prior salary.
- Health coverage for you and family in many locations.
- Flexible locations and schedules for many roles.
- Generous vacation days each year.
- Donate up to $2000 (or local currency) matched by the company.
- Up to 40 hours/year for volunteer projects.
- Parental leave minimum of 16 weeks.
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