AI Enablement Lead
Leads internal AI enablement by building agents, automations, and workflows to boost productivity across teams. Drives adoption through workshops, playbooks, and strategy execution; requires 4-8 years experience with hands-on LLM development and cross-functional enablement.
What You'll Do
Build & Deploy
- Design, build, and iterate on AI agents, automations, and workflows that solve real business problems across every function (engineering, sales, ops, marketing, CS, and more)
- Evaluate and implement AI tooling across the company — from identifying candidates to running pilots to making the call
- Build and maintain an internal library of prompts, playbooks, and reusable AI components that teams can self-serve from
Enablement & Uplevel
- Own the evolution of our AI Enablement program — take the company from baseline AI proficiency to advanced, function-specific use cases
- Embed with individual teams to identify where they can be even more efficient, then build or facilitate solutions — not one or more
- Collaborate with "AI champions" within each team who can sustain and extend AI adoption without depending on you
- Create and maintain enablement content: guides, templates, workshops, and async resources tailored to both technical and non-technical audiences
Strategy & Execution
- Partner closely with the Director of AI to translate internal AI strategy into a concrete, prioritized execution roadmap
- Track and report on adoption metrics, productivity gains, and ROI across AI initiatives
- Stay on the leading edge of the AI tooling landscape and bring timely, opinionated recommendations to the team
- Contribute to governance and responsible use frameworks as AI becomes more deeply embedded in how we work
What We're Looking For
Required
- 4–8 years of experience in a technical and/or project management role, ideally with 2 years focused on AI adoption, AI engineering, or applied AI in a cross-functional context
- Hands-on experience building with LLMs — prompt engineering, agent workflows, RAG pipelines, and tool integrations (Claude, Codex, Cursor, or similar)
- Strong technical fluency: you can read and write code well enough to build and debug agent workflows, evaluate APIs, and work credibly alongside engineers — but you don't need to be a full-stack engineer
- Proven track record of driving technology adoption with non-technical stakeholders — you know how to make people actually change how they work
- Excellent communicator: equally effective in a 1:1 with an engineer, a workshop with a sales team, and a readout to leadership
- Self-directed and autonomous — you don't need a detailed playbook to get started, and you know how to prioritize in a fast-moving environment
Nice to Have
- Experience at a growth-stage startup where you've had to build programs from scratch
- Familiarity with workflow automation tools (n8n, Zapier, Make) and enterprise AI tooling (Glean, Notion AI, etc.)
- Background in solutions engineering, forward-deployed engineering, or internal consulting
- Experience designing and running structured training or enablement programs
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