Engineering Manager — AI-First Platform & Agent Teams

About LumiMeds LumiMeds is a fast-growing U.S.-based telehealth startup focused on weight management and long-term metabolic health. We are building the next generation of e-commerce and clinical infrastructure from the ground up. As an early-stage company, we move quickly, operate with limited layers, and expect high ownership from every team member. There is no bureaucracy here — decisions happen fast, priorities evolve, and builders thrive. We are a remote-first, globally distributed team that values clarity, accountability, and people who take initiative rather than wait for direction. Platform & Product Engineering — LumiMeds Location: Remote — partial US hours overlap required (minimum 4–5 hours daily overlap with US Pacific/Eastern) Seniority: Manager — Player/Coach What We're Building LumiMeds is a high-growth telehealth platform building the operating system for modern virtual care — an AI-accelerated clinical engine, a high-converting e-commerce storefront, a consumer mobile app, and intake infrastructure that moves at the speed our patients expect. We don't scale engineering by adding headcount. We scale by multiplying leverage — through better systems, better tooling, and better use of AI. Our engineers already orchestrate Claude agent teams in production. Your job is to raise the ceiling on what that means. The Role This is a player/coach role for an engineer-turned-manager who is serious about AI-native engineering. You will lead a team of 4–8 full-stack engineers and simultaneously operate as the team's resident expert in designing and running Claude agent teams — using coordinated AI agents as a structural force multiplier on engineering output. You are not here to run standups and update Jira. You are here to build a team that ships more, faster, at higher quality than any team its size should be able to — by treating AI agent orchestration as a first-class engineering discipline. You will spend roughly 40% of your time coding and in agent pipelines , and 60% managing, designing systems, and raising the team's AI literacy. What Makes This Role Different Most engineering managers run teams of humans. You will run a team of humans and a fleet of agents — and your ability to design, direct, and verify agent work is as important as your ability to manage people. We are not looking for someone who has used Claude or experimented with agents. We need someone who has built real agent pipelines under production pressure — who knows exactly where they break, how to recover, and how to design for reliability at scale. This is the core of the role. Break complex engineering initiatives into agent-executable subtasks with crisp acceptance criteria Design multi-agent pipelines — parallel subagents for feature branches, test generation, code review, and documentation — and stitch their outputs into production-ready deliverables Set the team's standards for when to use agents, how to prompt them effectively, how to verify their outputs, and when to override them Treat agent output as team output — you are accountable for everything the agents on your team produce Continuously raise the ceiling: as the models improve, you update the playbook What You'll Actually Do Lead and grow a high-performing engineering team. Hire, onboard, coach, and develop 4–8 engineers. Set clear expectations, give direct feedback, and build a culture where velocity and quality are not in tension. Design and operate Claude agent teams. Architect agent pipelines using the Claude Agent SDK to parallelize engineering work at scale — parallel feature development, automated test coverage, documentation generation, code review passes, and spec-to-implementation workflows. You know how to define subagent roles, manage inter-agent context handoffs, validate outputs, and escalate to human judgment at the right moments. Stay in the code. You are a working engineer. You write production code, review PRs with technical depth, debug hard problems, and pair with engineers on the work that needs a senior eye. AI augments your output — it does not replace your technical judgment. Set the AI velocity standard. Define how the team uses AI tooling — Cursor, Claude Code, agent pipelines — and push the frontier. You have strong, specific opinions about how to prompt effectively, which tasks to delegate to agents, and how to verify agent output before it ships. Own delivery end to end. Run sprint planning, resolve blockers, manage dependencies across product, clinical, and infrastructure. You own outcomes — not just process. Write tickets AI agents can execute. Your specs are precise, structured, and unambiguous — acceptance criteria, edge cases, API contracts, all present. Claude Code or a junior engineer can run with them without a sync. Your specs don't loop. Build and own consumer app and e-commerce systems. You've shipped full-stack consumer products end to end — mobile-backed apps, e-commerce storefronts, subscription billing, checkout flows. You understand high-conversion funnel architecture and have built or owned user behavior tracking infrastructure: event schemas, analytics pipelines, conversion funnels, retention dashboards. This is not adjacent to the role — it is the role. Build and own A/B testing infrastructure. Design and maintain the experimentation platform that powers product decisions — feature flags, experiment assignment, statistical significance tracking, and results dashboards. You've built this before for high-traffic web products. You understand holdout groups, novelty effects, and how to run clean experiments across checkout flows, onboarding, and clinical intake. Build the systems that make the team scale. Engineering standards, PR review norms, deployment practices, observability, incident response. You build the scaffolding once so the team doesn't rebuild it repeatedly. Collaborate cross-functionally. Partner with Product, Clinical, and Op