Engineering Manager — AI-First Platform & Agent Teams at Lumimeds. . Location: Remote. 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 Ops to translate requirements into engineering reality. You are the technical voice in roadmap conversations — not a scheduler, but a decision-maker.. . What You'll Own. . . Domain. Scope. . Engineering Team. 4–8 full-stack engineers — hiring, performance, growth. . Agent Team Operations. Claude agent pipelines for parallelized engineering work. . Delivery. Sprint execution, unblocking, cross-functional coordination. . Technical Standards. Code quality, PR norms, AI tooling standards, observability. . Core Platform. Clinical engine, e-commerce, subscription billing, mobile backend. . A/B Testing Platform. Experimentation infrastructure, feature flags, statistical tracking. . AI Infrastructure. LLM integration patterns, agent orchestration architecture. . . Required Skills & Experience. . Engineering Leadership:. . . 6+ years of software engineering experience, including 2+ years in a lead or management role. . Hands-on experience with . Node.js / TypeScript. backends and . Next.js / React. frontends — you can read, write, and review production code at a senior level. . Strong database fundamentals: . PostgreSQL. (schema design, migrations, query optimization), Redis. . . AI-Native Engineering (Non-negotiable):. . . Claude Agent SDK:. Demonstrated experience building and orchestrating multi-agent pipelines — decomposing tasks, defining subagent roles, managing context handoffs, validating agent output. . LLM Integration:. Production experience integrating LLMs into real systems — streaming, tool use, structured outputs, prompt engineering. . AI Dev Tooling:. Daily use of Claude Code, Cursor, or equivalent. You have built workflows around these tools, not just used them ad hoc. . You can articulate — with specificity — how agent orchestration changes what a small engineering team can ship. . . Experimentation & A/B Testing:. . . Proven experience designing and building web A/B testing platforms from the ground up — not just using third-party tools, but owning the infrastructure. . Deep understanding of experiment design: randomization, assignment consistency, statistical power, holdout groups, and avoiding novelty bias. . Experience running experiments across high-traffic consumer funnels (checkout, onboarding, pricing, landing pages). . Familiarity with feature flag systems (LaunchDarkly, Statsig, homegrown) and experimentation analytics pipelines. . . Consumer Product & Tracking:. . . Hands-on experience building consumer apps and e-commerce platforms end to end — storefronts, checkout, subscriptions, billing. . Built user behavior tracking infrastructure: event schemas, analytics pipelines, conversion funnels, retention analysis. . Familiarity with tools like Segment, Mixpanel, Amplitude, or equivalent homegrown tracking systems. . . Systems & Delivery:. . . Experience running engineering sprints, managing dependencies, and owning delivery timelines. . Ability to write engineering specs that AI coding agents and engineers can execute with minimal back-and-forth. . Familiarity with . AWS. (EC2, RDS, Lambda, S3), Vercel, GitHub Actions, and CI/CD pipelines. . . Compliance:. . . Working knowledge of HIPAA/SOC2 requirements — you understand how compliance shapes architecture decisions. . . English:. . . Fluent written and spoken English — all team communication is async in English (Slack, PRs, specs, docs). . . Candidate Qualifications. . . The player/coach instinct:. You want to manage, but you're not ready to stop building. You think leaving code entirely would make you a worse manager.. . AI-native, provably so:. You can show, concretely, how agent orchestration has changed your own output — examples, numbers, or a portfolio. Not just familiarity — results.. . High standards for output quality:. AI-generated code is your code. You are not the manager who merges anything that compiles. You have a verification practice.. . Direct communicator:. You give feedback clearly, make decisions without excessive consensus-building, and disagree with product or leadership when the technical reality demands it.. . High agency:. You identify problems, propose solutions, and execute — you don't wait to be managed.. . . Nice to Have. . . Experience in telehealth, DTC health, or a regulated healthcare environment. . You've built an internal agent framework or tooling layer that other engineers on your team used. . Shipped a consumer mobile app with measurable retention and a backend you owned. . Background in distributed systems or real-time infrastructure (WebRTC, event-driven architectures). . You've written a post, given a talk, or built something in public about AI-augmented engineering. . . Why LumiMeds. . AI as infrastructure, not a feature.. We've already rewired how we build around AI. You won't be evangelizing something new — you'll be operating at the frontier with a team that's already bought in.. . Real technical complexity.. Clinical state machines, real-time patient-provider flows, high-stakes billing, HIPAA. The problems are hard because the domain is hard.. . Small team, enormous leverage.. You won't manage through layers. Your decisions show up in production the same week.. . Direct impact.. The systems you build affect patient outcomes. That's not a cliché here — it's the constraint that makes the work matter.. How to Apply. . If this role sounds like a fit, we’d love to hear from you. Please submit your application in English and ensure your resume reflects relevant experience for the role.. . This position is open to candidates based in approved locations, depending on the role and business needs. Qualified applicants will be contacted for next steps.. . LumiMeds is an equal opportunity employer. We hire based on skills, experience, and alignment with our values.. . Please note: This role requires professional-level English communication and availability to work U.S. business hours.
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