# Senior Manager of AI Enablement

**Company:** [CodePath](https://hotfix.jobs/companies/codepath)
**Location:** Remote
**Role:** Other
**Salary:** $110k – $150k/yr
**Experience:** 5+ years
**Skills:** LLM APIs, Claude, Prompt Engineering, Evaluation Design, Agent Frameworks, Mcp Integrations, Automation, Google Workspace, Slack, Notion, Asana, HubSpot, Zendesk
**Posted:** 2026-06-27

> Senior Manager of AI Enablement embeds with teams at CodePath to audit workflows, rapidly build and productionize LLM-powered agents and automations using Claude and other tools, coach teams to AI self-sufficiency, and drive measurable operational impact. Requires 5+ years automation/ops experience with recent hands-on LLM work, systems thinking, and ability to work with non-technical stakeholders.

## Job Description

## 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).

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