Forward Deployed AI Architect; US Remote

The Forward Deployed AI Architect sits with a team, learns how their work actually happens, and then rebuilds that work with them using AI. Reporting to the Sr. Director of AI + Digital Transformation, with a close relationship to the Direct, AI Platform Operations, this role takes prioritized processes from across the Alzheimer’s Association and makes them agentic, in whole or in part.

Each engagement is a sprint. Weeks to a few months, one process at a time, sometimes reaching across several business areas. The work starts with sitting next to people and watching what they actually do, at a level of detail needed for true transformation. It ends with something running that gives hours back, documentation the team can live with, and a clean handoff to AI Platform Operations and IT.

This is a builder role. You will spend your days inside our AI platforms (primarily Claude) shipping working solutions rather than recommending them. When we need something outside our existing technology stack, you will say so and find what that is. Every hour this role gives back to the Association and our staff goes somewhere meaningful. Toward care, toward being in community, toward the research that ends this disease—toward the work only a person can do.

• Process Discovery:
  Embed with a team and learn their work in granular detail. Sit through the actual task. Map where the time goes, where errors creep in, and which parts of the job people dread. Bring the team into the redesign from the first day so they own what comes out of it.
• Building:
  Build working agents, automations, skills, and tools using approved AI platforms, primarily Claude. Ship something people can use inside the sprint. Work in real time alongside the staff who will use it, iterating on their actual deliverables rather than a sample.
• Sprint Delivery and Handoff:
  Run each engagement as a time-boxed sprint with a defined start and end. Set the value target up front. Prove it at the close. Hand the solution to AI Platform Operations and IT with the documentation, test cases, and runbook they need to support it, then stay available through a 30-day stabilization window before moving to the next process.
• Troubleshooting:
  Diagnose and fix what you built while a sprint is live and through stabilization. After that, partner with the standing IT support group on resolution rather than owning it. Feed every failure back into how the next thing gets built.
• Reuse and Pattern Library:
  Recognize when a solution built for one team fits four others. Turn one-off builds into reusable skills, agents, and templates. Maintain a working library that the AI Collective and staff across the Association can pull from without asking permission.
• Value Measurement:
  Define a measurable target for every engagement before the work starts, whether that is hours returned, cycle time reduced, or capacity created. Track it through delivery and after. Report results to the Sr. Director and the AI Steering Committee, including the engagements that did not pay off.
• Responsible Deployment:
  Work inside the Association’s Responsible AI guidelines, data handling standards, and information security requirements. Know which processes should stay in human hands and say so early. Partner with Enterprise Risk and AI Platform Operations before any solution touches constituent, donor, research, or staff data.
• Cross-Functional Partnership:
  Maintain a close working relationship with the Director of AI Platform Operations, who owns platform configuration, enterprise connectors, security review, and consumption. Coordinate early when a build needs new system access or new credentials. Serve as a dedicated member of the AI Collective.