AI Enablement Lead

We are looking for a hands-on AI Enablement Lead to help our team actually use AI — not talk about it. This is a doer role for someone who already lives inside tools like Claude, Cursor, and the broader agentic ecosystem, and who gets a kick out of showing a skeptical colleague how to shave hours off their week. You’ll sit close to the work, embed with teams across the company, and turn “we should try AI for this” into shipped, repeatable workflows. You’ll also be our eyes and ears on a landscape that changes weekly, bringing the best of it back to the org in a form people can actually adopt. This isn’t a strategy-deck role. It’s a roll-up-your-sleeves role for a practitioner.
Responsibilities:

• Build and ship AI workflows by partnering directly with people across operations, marketing, sales, finance, support, and engineering to identify painful or repetitive work and rebuild it around AI.
• Be the in-house expert by running office hours, pair sessions, lunch-and-learns, and Slack-based support.
• Build prompts, projects, skills, and agents, maintaining a living library of reusable prompts, Claude Projects, Cursor rules, custom skills, and small automations.
• Track the landscape by staying on top of new model releases, tool updates, and techniques.
• Measure what works by tracking adoption, time saved, and quality improvements in concrete terms.
• Raise the floor and the ceiling by creating lightweight training and documentation that brings everyone up to a baseline of AI fluency.
• Keep it safe and sensible by partnering with security, legal, and IT on practical guardrails.

Requirements:

• 3-6 years of professional experience in a hands-on role (engineering, ops, analytics, product, technical PM, consulting, or similar).

Required Skills:

• Real, daily experience with Claude — Projects, Artifacts, MCP, Claude Code, or the API.
• Real, daily experience with Cursor — rules, composer, agent mode, MCP integrations.
• Comfort with at least light scripting (Python, JavaScript, or similar) and reading code well enough to modify it.
• Strong prompt engineering instincts and an understanding of how to get reliable output from frontier models.
• Experience building workflows that combine LLMs with APIs, documents, spreadsheets, or internal tools.
• A teacher’s temperament — patient, clear, and good at meeting people where they are.
• Bias to action — you’d rather ship a rough v1 today than a polished v1 next month.

Preferred Skills:

• Experience with other frontier tools (ChatGPT/Codex, Gemini, Copilot, v0, Replit Agent, Windsurf, etc.).
• Experience with agent frameworks, MCP servers, RAG, or evals.
• Hands-on experience orchestrating multiple agents or sub-agents for non-trivial workflows.
• Familiarity with our tech stack — Java, Spring Boot, Angular, and .NET — is a strong bonus.
• Background in ops, revenue operations, or internal tooling.
• A public footprint — blog, GitHub, newsletter, demos — showing how you think about AI.