Elastic
Enterprise · Search
- HQ
- Mountain View, US
- Founded
- 2012
- Website
- elastic.co
Enterprise · Search
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.
Currently tracking 16 active AI roles, up 55% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $192k–$593k (avg $307k).
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, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining how enterprises build, manage, and scale context for AI agents. This role involves understanding customer requirements, building a roadmap for context engineering capabilities, and working with data science and engineering on benchmarking and evaluations. | Agent | 8 |
| Principal Product Manager, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining strategy and roadmap for context engineering capabilities for AI agents. The role involves understanding customer requirements, market trends, and working with data science and engineering teams to develop strategies for agent benchmarking and evaluation, as well as user experience design. | Agent |
| 8 |
| Principal Product Manager, AI agents - Search Principal Product Manager for Elastic's Agent Builder, focusing on defining the vision, strategy, and execution for how enterprises build, manage, and scale context for AI agents. This role involves understanding customer requirements, building roadmaps for context engineering capabilities, and working with data science and engineering on benchmarking and evaluations. | Agent | 8 |
| Principal Product Manager, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining how enterprises build, manage, and scale context for AI agents. This role involves understanding customer requirements, building roadmaps for context engineering capabilities, and working with data science and engineering on agent benchmarking and evaluations. | Agent | 8 |
| Principal Product Manager, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining strategy and execution for context engineering capabilities for AI agents. The role involves understanding enterprise customer needs, market trends, and working with data science and engineering teams to build and evangelize agent capabilities. | Agent | 8 |
| Principal Product Manager, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining how enterprises build, manage, and scale context for AI agents. This role involves understanding customer requirements, building a roadmap for context engineering capabilities, analyzing the AI Agent market, and working with data science, engineering, and design teams. The goal is to make AI agents faster, lower cost, and more accurate by enhancing their context layer. | Agent | 8 |
| 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, AI agents - Search Principal Product Manager for Elastic Agent Builder, focusing on defining strategy and execution for context engineering capabilities for AI agents. This role involves understanding customer requirements, market trends, and working with data science and engineering teams to build and evangelize agent context solutions. | Agent | 7 |
| Principal Product Manager AI-driven, Observability Principal Product Manager for AI within the Observability team, driving the vision and execution of AI-powered features. The role focuses on Agentic AI, Machine Learning, LLMs, and semantic context to transform the observability lifecycle, including data onboarding, enrichment, root cause analysis, impact assessment, and automated remediation. Responsibilities include defining AI strategy, owning the roadmap for embedding AI/ML into workflows, partnering with engineering and UX, collaborating with sales/marketing, engaging with customers, and tracking industry trends. | 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 |