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AI Enablement & Workflow Innovation Lead About Canopy Canopy is a healthcare safety technology company building the connected safety platform for healthcare teams. Our products help hospitals and health systems protect frontline staff, respond faster in high-intensity environments, and create safer places to work. We're at an important stage of growth: scaling our products, our operating systems, and the way our teams work together. We believe AI can help us move faster, improve quality, and create more space for higher-impact thinking, but only if it's adopted thoughtfully, securely, and practically. This role exists to make Canopy an AI-native company in how we build, operate, support customers, and make decisions. This is a hybrid role in the New York City metro area. About the Role We're hiring an AI Adoption Accelerator: someone who lives at the frontier of agentic AI and can pull the rest of the company up to that frontier with them. You do not need to be a career software engineer. You do need to be the person who's already built a dozen agents, knows how the current frontier models differ in practice, has strong opinions about context engineering, can stand up an MCP server in an afternoon, and won't ship an agent without an eval behind it. And you need to be able to sit next to someone who has never written a prompt and leave them able to build the next workflow themselves. The job has two halves, and they matter equally: Build . Embed with teams across Canopy (CX, Sales, Marketing, Product, Engineering, Operations, Finance, People), map their work, and turn the highest-leverage workflows into real AI tooling. Sometimes that's a Claude Project with the right skills and connectors. Sometimes it's a multi-step agent wired into our systems. Sometimes it's a sharp prompt that ends a problem someone has been dragging through their day for a year. Teach . Every build is also a tutoring session. By the time you ship something with a teammate, they should understand enough to build the next version without you. The goal is not to become the bottleneck, it's to leave behind people who can pattern-match on their own, and to compound Canopy's capability with every workflow. What you will own Building & shipping AI workflows . Design, build, and deploy AI workflows that range from lightweight Claude Projects with custom skills to full multi-step agentic systems. Build and integrate MCP servers and connectors so our agents reach into the tools people already use: Slack, Salesforce/HubSpot, Zendesk, Gong, Google Workspace, internal APIs, our own products. Reach for the right tool for the job, including no-code tools when that's genuinely all a problem needs, without over-engineering. Operating rhythm & experimentation . Establish a lightweight model for how AI experiments happen at Canopy: intake, prioritization, concise experiment briefs, demos, documented learnings, and clear scale-or-kill decisions. Partner with the early-adopter group to pick 2–3 high-impact workflows per quarter. Run a regular demo cadence where teams show what they built, what worked, and what others can reuse. Enablement & teaching . Build workflow-based learning experiences that help people use AI in their actual day-to-day work, tailored by role. Run office hours, workshops, and "build with me" sessions. Produce reusable assets (prompt libraries, workflow templates, playbooks, starter kits, demo recordings) that let teammates extend AI work without you. Teach not just how to use AI, but when to, when not to, and where human judgment has to stay central. Governance, evals & responsible use . Develop eval practices so we know our agents actually work, and keep working as models change underneath us. Partner with Security, Legal, and People to keep AI usage safe and compliant, with real guardrails around PHI, customer data, and regulated workflows. Build the habits