Principal AI Ecosystem Architect

Elastic

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
San Francisco, CASeattle, WA
Salary
$184,200–$291,400 / yr
Posted
58 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $230k
This role $238k
$171k most similar roles pay here $304k

This role pays more than 58% of similar roles. Most pay $184,900–$275,570 — the shaded band above. At the midpoint, this role pays about $238k versus about $230k for comparable roles.

Based on 239 similar postings.

Employer

About Elastic

Elastic is the company behind Elasticsearch and the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). It sells search, observability, and security products built on that search engine, primarily through its Elastic Cloud managed service.

Elastic currently has 240 open roles on FindRole.

Listed pay typically runs $133,100–$210,600 across 91 roles with salary data.

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At a glance

TL;DR · Principal AI Ecosystem Architect

Role Posting Log in to save

Principal AI Ecosystem Architect - OpenAI/Anthropic As a member of the Ecosystem Architects team, you will serve as a hands-on individual contributor responsible for managing and owning technical relationships with OpenAI and Anthropic. You will drive co-build strategies by identifying integration priorities, building reference architectures, and developing prototypes that demonstrate Elasticsearch as a retrieval layer for agentic AI workflows. Your role involves influencing product roadmaps based on gathered technical signals, creating go-to-market content like solution briefs and technical guides, and representing the company at developer conferences. You will leverage expertise in context engineering for AI agents, security operations, and observability to solve the problem of bringing frontier intelligence to unstructured enterprise data. The ideal candidate possesses experience in technical presales or partner engineering and can navigate complex integrations between search technology and large language model ecosystems.

Skills

Elasticsearch OpenAI Anthropic Agentic Workflows Security Observability Context Engineering Product Strategy Reference Architecture Integration technical presales Solutions Architecture

What you'll do

  • Drive co-build strategies with the Product team to integrate retrieval, security, and observability capabilities into OpenAI and Anthropic ecosystems.
  • Serve as the primary technical point of contact for both OpenAI and Anthropic to represent Elasticsearch's role in agentic workflows.
  • Build reference architectures and working prototypes that demonstrate Elasticsearch as a retrieval layer for AI agents.
  • Influence Elastic’s product roadmap by providing technical signals gathered from partner teams and customer needs.
  • Manage executive-level relationships with partners to align on progress, priorities, and investment focus.
  • Co-author joint solution briefs, technical guides, and co-branded content to showcase the value of integrated AI solutions.
  • Represent Elastic at AI-focused events, conferences, and community forums to engage with a practitioner audience.
  • Translate technical integrations into marketing materials and enablement tools for the sales team and customers.

What we're looking for

  • 7+ years of experience in technical presales, partner engineering, solutions architecture, or product management.
  • Proven experience owning technical relationships with strategic AI or platform partners as the named point of contact.
  • Hands-on experience building prototypes and integration demos to validate ideas with partner and product teams.
  • Track record of influencing product roadmaps and partner priorities.
  • Strong communication skills for presenting at developer conferences and collaborating with partner engineers.
  • Willingness to travel 30% to partner offices, events, and conferences.
  • Direct experience working with OpenAI or Anthropic in a technical capacity (preferred).
  • Technical depth in context engineering for AI agents, AI-powered security operations, or AI-powered observability (preferred).

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