Lumimeds - Engineering Manager — AI-First Platform & Agent Teams

• 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 • Node.js / TypeScript • Next.js / React • 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 • Claude Agent SDK: • LLM Integration: Production experience integrating LLMs into real systems — streaming, tool use, structured outputs, prompt engineering • LLM Integration: • AI Dev Tooling: Daily use of Claude Code, Cursor, or equivalent. You have built workflows around these tools, not just used them ad hoc • AI Dev Tooling: • 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: • 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) • 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. • The player/coach instinct: • 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. • AI-native, provably so: • 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. • High standards for output quality: • Direct communicator: You give feedback clearly, make decisions without excessive consensus-building, and disagree with product or leadership when the technical reality demands it. • Direct communicator: • High agency: You identify problems, propose solutions, and execute — you don't wait to be managed. • High agency: • 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