Senior Manager of AI Enablement

What You'll Do

• Embed and audit: Rotate through functions, audit how teams work, map repetitive tasks, and identify highest-leverage automation opportunities.
• Build the v1 fast: Develop task-specific agents and automations (e.g., research synthesis, status updates, partner reporting, monitoring) using Claude, Claude Code, MCP integrations, and tools like Google Workspace, Slack, Notion, Asana, HubSpot, Zendesk.
• Productionize and set quality gates: Convert prototypes into production-grade tools with rubrics, evals, and review steps to prevent output drift.
• Build reusable assets: Create skills, plugins, and templates for teams to self-serve, and maintain them as tools evolve.
• Coach to self-sufficiency: Teach through building alongside people, meet teams at their AI proficiency level, and leave them more capable.
• Measure, report, and rotate: Track outcomes like time saved and quality gained, present to leadership, document, hand off, and move to next function.

Requirements

• 5+ years in automation/ops tooling, including recent hands-on LLM/agent work in a professional setting.
• Hands-on proficiency with LLM APIs (e.g. Claude) and low-code/no-code agent frameworks.
• Strong understanding of prompt engineering and evaluation design.
• Systems thinker who can identify automatable steps in workflows and connect disconnected pieces.
• Ability to embed with non-technical teams, earn trust quickly, and translate pain points into solutions.
• Strong taste and judgment on AI output quality; ability to build guardrails against mediocre results.
• Clear written and verbal communication skills across all levels of AI proficiency.

Preferred

• Experience deploying Claude or another enterprise AI assistant across a largely non-technical organization.
• Familiarity with MCP integrations and agent architecture patterns.
• Background in change management or internal transformation programs.

What This Role Is Not

• A software engineer (no building infrastructure or shipping product code).
• Purely a trainer (teaching is through building alongside teams).
• A researcher (evaluation serves engagements, but core is building, deploying, iterating).