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DocPlanner is a healthcare platform operating in 13 countries, serving 90+ million patients monthly and 300k+ specialists. The company is reinventing product development with AI-assisted engineering and is undergoing a major architectural transformation.
You will be a Staff Engineer owning the technical direction of the Marketplace—the patient-facing platform where millions search for doctors, compare profiles, and book visits. The Marketplace is mid-migration from a long-lived PHP monolith into a company monorepo built from vertical slices (API + React web), using a strangler pattern. Booking flows, doctor profiles, listings, and Q&A are already on this path; search is being built natively on it.
Your core mission: ensure this migration results in a better platform, not just a relocated one. Marketplace capabilities should become clean, well-owned building blocks that other Docplanner products can plug into through clear contracts. You will use AI coding agents (like Claude Code) to prototype and ship production changes, owning design, review, and quality bars. Your influence comes from decision quality and how much you elevate teams around you.
In 6 months, success looks like: a written, agreed technical direction for Marketplace migration (which domains move next, in what order, what "done" means); at least one core capability (e.g., bookings) exposed through a clear, versioned contract consumed in production by another product; measurable monolith shrinkage with fewer ad-hoc endpoints and more domains where the monorepo is source of truth; you personally shipping with AI agents writing code while you own design and review; AI-assisted workflows for migration and integration proven in one team and adopted by others.
You will own the target architecture across search, listings, doctor profiles, and booking flow. Shape the monolith-to-monorepo migration strategy, deciding which domains move next and how to move them safely (strangler routing, anti-corruption layers, shadow traffic, staged source-of-truth flips). Move domains from "thin proxy over monolith" to "owned natively in monorepo" (data, business logic, persistence). Make Marketplace easy to integrate by turning capabilities into reusable building blocks for the whole portfolio.
You will lead through AI-native engineering: ship production changes by directing AI coding agents, prototype risky migration/integration parts yourself, then hand teams a proven path. Drive AI-assisted development for migration work—understanding legacy code, generating contracts, adapters, tests, keeping parity between old and new. Help make Marketplace capabilities usable by AI agents as well as people.
You will multiply teams around you: partner with Engineering and Product Managers on planning and unblocking cross-team work. Mentor senior engineers on architecture, system design, and pragmatic decision-making. Contribute to DocPlanner's Staff+ community of practice.
REQUIREMENTS:
- Led technical direction across several teams (not just one), with decisions that held up in production
- Taken large legacy systems apart while they kept serving real traffic; know strangler pattern, anti-corruption layers, data migration, dual-write pitfalls from hands-on experience
- Strong in distributed systems and backend architecture; comfortable in polyglot environments
- Solid hands-on experience using AI to accelerate software development, with good judgment on when to rely on it and when not to
- Moved from writing code by hand to directing AI agents that write it; can demonstrate how you keep design, correctness, and security under control
- Enjoy mentoring and raising the bar of engineers around you
- Fluent English
BONUS:
- Experience with two-sided marketplaces, search and discovery, or booking/scheduling systems
- Experience with monorepos at scale (build tooling, code ownership, shared platform conventions)
- Have exposed product capabilities to AI agents
- Healthcare or other regulated domain experience (data privacy and security shaping architecture)
Company values impact over company size.
