Elastic
Enterprise · Search
- HQ
- Mountain View, US
- Founded
- 2012
- Website
- elastic.co
Enterprise · Search
Currently tracking 16 active AI roles, up 55% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $192k–$593k (avg $307k).
Elastic has 28 active AI-related job listings, with a significant focus on roles related to agents, which constitute 86% of their openings. The majority of these positions are within Engineering. The company is hiring across the United States, United Kingdom, and Canada. Recurring technical tags include vector_db, RAG, and model_serving, suggesting a focus on building and deploying AI applications that leverage external knowledge.
Elastic currently has 30 active AI-related roles in our index. The most common open titles are: Senior Software Engineer - Search Relevance in ES|QL - Elasticsearch (6), Principal Software Engineer - Vector Search - Elasticsearch (5), Senior Software Engineer - SSC (4), Principal AI Ecosystem Architect - OpenAI/Anthropic (2), Principal Product Manager Agents and Context - Elasticsearch (2). Most positions are in Engineering and Research.
Elastic's active AI hiring is concentrated in: agents (87%), application (10%), serving infrastructure (3%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Elastic is hiring AI talent in: United States (16 roles), United Kingdom (7 roles), Spain (4 roles), Canada (3 roles).
Job postings at Elastic most frequently mention: Observability, Data Governance, Content Generation, Cloud Security, Cloud Infrastructure.
In the past 30 days, Elastic has posted 23 new AI-related roles. That is a +44% change versus the prior 30 days (16 → 23).
| Title | Stage | AI score |
|---|---|---|
| Principal Product Manager Agents and Context - Elasticsearch Principal Product Manager for Elastic's Agent Builder, focusing on context engineering for AI agents. The role involves defining strategy, roadmap, and execution for capabilities that make AI agents faster, cheaper, and more accurate. It requires deep understanding of the AI/ML landscape, including LLMs, RAG, and vector databases, and involves working closely with customers, sales, engineering, and data science teams. | Agent | 7 |
| Principal Product Manager Agents and Context - Elasticsearch Principal Product Manager for Elastic Agent Builder, focusing on defining the vision, strategy, and execution for context engineering capabilities that enable enterprises to build, manage, and scale AI agents. The role involves understanding customer requirements, market trends, and working with data science and engineering teams to benchmark and evaluate agent capabilities, with a strong emphasis on RAG architectures and vector databases. |
| Agent |
| 7 |