Omada Health is on a mission to inspire and engage people in lifelong health, one step at a time. The Omada IT department builds and operates resilient, scalable services that empower everyone at Omada. Increasingly, that means putting the right AI capabilities in the right people's hands
Job Overview: The Senior Forward Deployed AI Engineer is a senior individual contributor who builds and expands Omada's MCP ecosystem, connecting SaaS tools and internal systems via MCP servers, writing skills, composing tool bundles for different teams, and deploying them to the right people. You are the bridge between what AI can do and what Omada's teams actually need it to do
You will work directly with department champions across the company to understand their workflows, surface opportunities for AI-driven automation, and turn those opportunities into real, working integrations. Your daily question is: what new capability did I unlock for the company today? This role sits on a small, high-impact team within IT that owns business process automation and agentic/AI-driven automation. You'll partner with Senior IT Engineers, Automation and work under the Senior Manager, IT Automation. We're hiring two people for this role
You'll use Omada's MCP control plane, not as a system to babysit, but as the platform that lets you move fast and ship integrations safely. You build with security and governance in mind from the start because it's the right way to build, not because someone else is watching the dashboards
And you’ll document and socialize as you go, so the entire IT org understands this emergent technology and can multiply your impact throughout the organization
Responsibilities: AI Enablement & Adoption Serve as the primary point of contact for department champions across Omada, working with them to understand their day-to-day workflows and identify where AI-assisted automation creates real leverage
Drive AI adoption across the company by deploying tool bundles that are actually useful, making sure integrations fit how teams work rather than asking teams to adapt to what's technically convenient
Run a continuous feedback loop: gather usage signals and qualitative input from champions, identify what's working and what's falling flat, and iterate accordingly