AI Operations Engineer, Partnerships
$143k - $160k • Remote • San Francisco, CA
Posted 14h ago
About the job
Our Partner Experience team is building an AI-native operating model that includes a partner portal, CRM workflows, enablement and certification platforms, and tracking systems. This role will focus on designing, building, and running agentic workflows on top of these systems. You will create Claude-powered agents and automations to handle tasks such as triaging partner applications, drafting communications, syncing data across tools, and surfacing deal signals. This is a hands-on builder role where you will ship working automations weekly, own them in production, and continuously expand the team's capabilities without increasing headcount.
Responsibilities
- Design and build agentic workflows using Claude, MCP connectors, and API integrations to automate partner experience operations like application triage, onboarding, deal registration, certification tracking, partner communications, and reporting.
- Integrate automated workflows with the partner portal, CRM, enablement stack, finance systems, and databases, ensuring data consistency and avoiding shadow processes.
- Transform recurring manual tasks into reliable, monitored automations by defining workflows, building, testing, adding guardrails and human-in-the-loop checkpoints, and documenting their operation.
- Manage the operational health of deployed automations, including error handling, edge cases, escalation paths, and adapting to process changes.
- Rapidly prototype solutions by collaborating with the team and partner managers to identify high-friction workflows and deliver working versions quickly.
- Establish reusable patterns for skills, prompts, connectors, and playbooks to accelerate future workflow development and enable team self-service for simpler automations.
Requirements
- Hands-on experience building with LLMs and agentic tooling, including prompt and workflow design, tool/function calling, MCP or comparable integration frameworks, and evaluating agent output quality.
- Experience working with APIs and business systems such as CRMs, partner portals, LMS/certification platforms, spreadsheets, Slack, and email, and scripting integrations using Python or JavaScript.
- Strong judgment regarding automation risk, understanding when agents can operate autonomously, when human checkpoints are needed, and how to design for graceful failure.
- Process improvement skills to identify bottlenecks in manual workflows and redesign them for automation.
- Clear written communication skills for documenting built automations.