AI Operations Engineer, Partnerships

About the role

Our Partner Experience team is building an AI-native operating model. We already run a growing set of partner-facing systems: a partner portal, CRM workflows, enablement and certification platforms, and the trackers that connect them. The systems lead on our team owns that foundation — the portal, the data model, and the integrations that keep partner records accurate and flowing.

This role is the other half of that build. As our AI Operations Engineer, you'll design, build, and run the agentic workflows that sit on top of those systems: Claude-powered agents and automations that triage partner applications, draft and send partner communications, sync data across tools, surface deal and enablement signals, and take routine operational work off the team entirely. Where the systems lead builds the rails, you build what runs on them.

This is a builder role, not an analyst role. You'll ship working automations weekly, own them in production, and continuously expand what the team can do without adding headcount.

Key responsibilities:

• Design and build agentic workflows (using Claude, MCP connectors, and API integrations) that automate core partner experience operations: application triage, onboarding, deal registration, certification tracking, partner communications, and reporting
• Partner closely with our systems lead to integrate these workflows with the partner portal, CRM, enablement stack, finance systems, and database systems — consuming and writing back to the systems of record rather than creating shadow processes
• Turn recurring manual work into reliable, monitored automations: define the workflow, build it, test it against real cases, add guardrails and human-in-the-loop checkpoints where decisions carry risk, and document how it runs
• Own the operational health of what you ship: error handling, edge cases, escalation paths, and iteration when partner processes change
• Prototype fast with the team: sit with partner managers, find the highest-friction workflows, and get a working v1 in front of them in days, not quarters
• Establish reusable patterns (skills, prompts, connectors, playbooks) so each new workflow is faster to build than the last, and teach the broader team to self-serve on the simple ones

Minimum qualifications:

• Hands-on experience building with LLMs and agentic tooling: prompt and workflow design, tool/function calling, MCP or comparable integration frameworks, and evaluating agent output quality
• Experience working across APIs and business systems — CRMs (e.g., Salesforce), PRM/partner portals, LMS/certification platforms, spreadsheet-based tools, Slack, and email — and scripting the glue between them in Python or JavaScript
• Strong judgment about automation risk: knowing which steps an agent can own outright, which need a human checkpoint, and how to design for graceful failure
• Process instincts: ability to look at a messy manual workflow, find the actual bottleneck, and redesign it rather than just automating it as-is
• Clear written communication; documents what you build so it outlives you

Preferred qualifications:

• 5+ years in operations engineering, solutions engineering, business systems, RevOps, or a similar build-heavy role, ideally supporting a partner, sales, or customer success organization
• Experience in partner/channel operations specifically (deal registration, MDF/co-sell programs, partner tiering, certification pipelines)
• Experience shipping internal AI tools or automations that are still running in production today
• Familiarity with the Claude API, Claude Code, or agent frameworks; building custom MCP servers is a plus