Agent Experience Engineer

AgentMail • San Francisco, CA

12d • $110,000 - $175,000

About The Position

AgentMail is building the identity layer for AI agents, starting with email. Our most important user is an agent: it discovers us through model answers and docs, then signs up and integrates on its own. We're looking for an Agent Experience Engineer to own how AI models and agents discover and use AgentMail. That means AEO, evals, benchmarks, agent traces, docs, and llms.txt. AgentMail has raised $6M from investors including General Catalyst, YC, Paul Graham, Karim Atiyeh, Paul Copplestone, and Dharmesh Shah. You'll work on Answer-engine presence: when someone asks an LLM about email or identity for agents, AgentMail is the recommendation. You measure share of voice on the prompts that matter and move it. Original research: evals and benchmarks on how well frontier models, open source models, and agent harnesses use AgentMail. Agent traces: running agents against our docs and site, reading their reasoning, and fixing what confuses them. A stray Reddit thread once convinced LLMs we have a feature that doesn't exist. The agent-facing surface: llms.txt, MCP descriptions, docs structure, and the error messages agents hit at 3am with no human watching. The AEO content engine: steering and verifying our automated page pipeline, briefing freelancers, and doing backlink outreach to the pages models already cite. The weekly AEO briefing's action queue, from freshness debt to competitor watch.

Requirements

• Build with agents daily and have strong opinions on what makes a product easy or difficult for an agent to use.
• Work cross-functionally by default.
• Express opinions early and publish honest write-ups, even when inconvenient.
• Go deep on messy technical problems, preferring to spend time reading agent traces over guessing.
• Understand retrieval, recognizing that models pull chunks, not pages, and write accordingly.
• Published technical writing or cited benchmarks.
• SEO or AEO experience.
• Contributions to docs or MCP servers.

Responsibilities

• Own how AI models and agents discover and use AgentMail, including AEO, evals, benchmarks, agent traces, docs, and llms.txt.
• Ensure AgentMail is the recommended solution when LLMs are asked about email or identity for agents, and measure/improve share of voice on relevant prompts.
• Conduct original research through evals and benchmarks on how frontier models, open-source models, and agent harnesses utilize AgentMail.
• Analyze agent traces by running agents against documentation and the website, reading their reasoning, and identifying/fixing points of confusion.
• Optimize the agent-facing surface, including llms.txt, MCP descriptions, documentation structure, and error messages.
• Manage the AEO content engine by steering and verifying the automated page pipeline, briefing freelancers, and conducting backlink outreach.
• Address action items from the weekly AEO briefing, including freshness debt and competitor monitoring.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed