Chief of Staff

Posted 43ds ago

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Job Description

Chief of Staff responsible for operationalizing CEO's AI-Native MSPbots vision. Leading automation of executive functions and driving internal alignment across departments.

Responsibilities:

  • AI-First Business Operations (The "Automator") Dogfooding & Transformation: Actively replace internal manual processes (Marketing, CS, Ops) with MSPbots’ own AI agents and RPA tools.
  • Office of the CEO Automation: Build and maintain AI workflows to filter CEO emails, summarize L10 meetings, and pre-draft responses. Goal: Reduce CEO operational load by 40% within 6 months.
  • Governance & Safety: Enforce the AI governance framework. Ensure all internal AI agents have correct permissioning, audit logs, and "human-in-the-loop" fail-safes before scaling.
  • Strategy Execution & EOS Management (The "Integrator Proxy") L10 & Rhythm: Owner of the CEO’s L10 meeting. You do not just take notes; you audit the Scorecard data for accuracy before the meeting and force resolution on "Issues."
  • Rocks Management: Track progress on quarterly Rocks across departments. Use BI dashboards to validate "Done" status (no verbal updates without data).
  • Cross-Department Alignment: act as the "API" between the Visionary (CEO) and the department heads. Translate high-level vision into execution tickets with clear owners and deadlines.
  • Special Projects & GTM Experiments Launchpad: Lead rapid-fire GTM experiments for new AI features. Define success metrics (CAC, Adoption %, Churn impact) and kill projects fast if data fails.
  • Feedback Loops: Institutionalize the feedback loop between Product and Customer Success. Ensure ticket data is structured and fed back into Product R&D for agent training.

Requirements:

  • Must-Haves:
  • AI Pragmatist: Expert level proficiency with LLMs (Claude/GPT-4) for complex workflow construction. You don't just "chat"; you build structured prompts, chain-of-thought workflows, and agentic systems.
  • Technical Literacy: Ability to read API documentation, understand webhooks, and ideally write basic Python/scripts to glue systems together (or effectively manage devs who do).
  • Data-Native: Fluent in BI concepts. You don't ask "how are sales?"; you query the dashboard for "MRR growth vs. last month" and identify the variance.
  • EOS Familiarity: Experience working in (or running) an EOS environment (Level 10s, V/TO, Accountability Chart).