Senior Engineering Manager, Co-Intelligent Coaching

Omada Health is on a mission to bend the curve of chronic disease. Job overview: Co-Intelligent Coaching is how Omada builds the future of coaching support. AI owns the member moments that run around the clock: goal setting, food guidance, reflection, and unblocking the daily challenges that happen between sessions. That frees our human coaches to do what only they can. They build real relationships and deliver care when it matters. We are hiring a Senior Engineering Manager to own a significant piece of Omada's Co-Intelligent Coaching. You own what gets built, in what order, and how the people building it grow. A squad owns problems from prototype to production, including the maintenance and the on-call rotation for what it ships. At this level you own more than one, which means the hardest calls you make are the ones about where capacity goes when two good things want it at the same time. You stay technical. You are in the codebase and in the same agent workflows your builders use, close enough to review architecture, catch a weak design, and be useful in an incident. Where you manage directly, you ship production work off the critical path. Where you manage through someone else, that person's growth is your work product. You partner with Product Strategists who spend their time in front of members, coaches, and stakeholders, and who prototype to test ideas quickly. They own what gets built and why. You own whether it can be delivered, at what cost, and by when, and you are senior enough that your answer shapes the roadmap rather than just responding to it. About you: You have built AI products, not just used AI to build them. You have shipped agents to production and lived with how they behave at scale. You measure quality with evals: when you change a prompt or swap a model, you can prove whether it got better. You are comfortable being accountable for what your squads ship. You still write code, and you want to. This role ships production work off the critical path, in the same codebase and the same agent workflows as your squads, so you feel the friction your people feel first-hand. You have a point of view on where AI-assisted development helps and where it creates rework, and it comes from changing how a real team works, not from reading about it. You have done the engineering manager job well enough that you can teach it. Whether or not you have carried the title of manager-of-managers, you have grown someone into leading, and you know the difference between doing the work for them and raising their ceiling. Your first team is your peer group, not your reports. When something is slowing down the engineering org and it is nobody's job, you have a track record of picking it up, getting the right people in the room, and finishing it. What you'll be doing: • Own the member experience that runs around the clock. AI handles the moments between sessions: goal setting, food guidance, daily reflection. You own where it hands off to a human coach, and your squads own all of it from prototype to production. • Own delivery across your squads. Sprint shaping, prioritization, backlog grooming, and estimation. Make the calls, write them down, and be accountable for them. When two squads want the same thing at the same time, you are the one who decides. • Own cycle time. Yours to improve, not at the expense of quality, and yours to explain when it changes, including why one of your squads is slower than the other. • Stay technical. On squads you manage directly, you ship production work every sprint, off the critical path, in the same agent workflows your builders use. On squads that run through a manager, you stay close enough to review architecture, catch a weak design, and be useful in an incident. Either way, you can