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 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 |