As the Agent Experience (AX) Specialist, you’ll pioneer how AI agents engage with our platform. This role is central to making sure automated systems can independently find, understand, and utilize our tools—without relying on human intervention.
What You'll Do
- Own the end-to-end experience AI agents have when interacting with our MCP infrastructure, from initial discovery to full integration.
- Refine tool metadata, error handling, and registry entries so agents interpret capabilities accurately and call them appropriately.
- Test how major AI platforms recommend our tools compared to others, measuring inference share trends and identifying adoption barriers.
- Design and maintain dashboards that connect agent activity to user registrations and product usage, defining the key stages of the AX funnel.
- Create documentation, example repositories, and structured content tailored for machine parsing—not just human readers.
- Run experiments to determine which configurations, descriptions, or formats lead to higher engagement and adoption by agents.
- Use logs, APIs, and analytics to track connections, extract insights, and maintain data accuracy across reporting systems.
Requirements
- Deep understanding of MCP: how servers operate, how agents discover tools, and how context is exchanged.
- Ability to edit MCP tool definitions, JSON schemas, and registry metadata independently.
- Hands-on experience using at least two major AI coding agents in real workflows.
- Skill in analyzing agent decision logic—especially how tool descriptions, parameters, and errors influence tool selection.
- Proficiency with npm: publishing packages, updating metadata, interpreting download trends.
- Strong Git and GitHub skills: cloning, editing, PRs, and maintaining public examples.
- Experience working with REST APIs, OAuth flows, and JSON-based configurations.
- Ability to write queries against server logs to extract usage patterns and connection data.
- Experience setting up custom analytics reports, tracking events, and building funnel visualizations.
- Understanding of attribution challenges when agent interactions bypass traditional web tracking.
- Ability to design and interpret A/B tests without relying on data science support.
- Commitment to rapid iteration—weekly deployments are expected, not aspirational.
- Clear grasp of how agents consume content: structured data, direct answers, and upfront code examples matter most.
- Experience writing technical docs optimized for machine reading: explicit capabilities, structured headings, and comparison clarity.
- Knowledge of the difference between SEO and GEO—how content ranks in search versus how it’s cited by agents—and the ability to produce both.
Preferred Qualifications
- Familiarity with media management APIs for image and video processing.
- Experience with GEO-focused tools like Profound, Otterly.AI, or Ahrefs Brand Radar.
- Background in developer marketing, developer relations, or growth in developer-focused tooling.
- Understanding of the cloud-based media solutions landscape and key competitors.
- Hands-on work building or contributing to MCP servers.
- Python scripting skills for automation and data analysis tasks.
