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DocPlanner (formerly Doctoralia) 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 own the technical direction of the Marketplace—the patient-facing platform where millions search for doctors, compare profiles, and book visits. The Marketplace is migrating 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 in progress; the new search experience is being built natively on the new stack.
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. When a patient books a visit, other systems (patient engagement, AI assistants) should know about it through a clear contract, not one-off integrations.
You will direct AI coding agents (such as Claude Code) to build, own design and review, and set the quality bar. You prototype the hard parts yourself and show teams how far the approach can go. Your influence comes from the quality of your decisions and how much you make teams around you better.
In 6 months, success looks like: (1) a written, agreed technical direction for the Marketplace on the monorepo with a realistic plan for making it the source of truth for bookings; (2) at least one core capability (e.g., bookings) exposed through a clear, versioned contract that another Docplanner product consumes in production; (3) the monolith shrinking measurably with fewer ad-hoc endpoints and more domains where the monorepo is the source of truth; (4) you personally shipping with AI agents writing code while you own design, review, and quality; (5) AI-assisted workflows for migration and integration proven in one team and adopted by others.
You will own the technical direction across search, listings, doctor profiles, and booking flows. You will shape the monolith-to-monorepo migration, deciding which domains move next, how to move them safely (strangler routing, anti-corruption layers, shadow traffic, staged source-of-truth flips), and when a domain truly counts as migrated. You will move domains from "thin proxy over the monolith" to "owned natively in the monorepo," including data, business logic, and persistence. You will make the Marketplace easy to integrate with by turning capabilities into reusable building blocks.
You will ship production changes by directing AI coding agents, prototype the riskiest parts of migrations or integrations, and hand teams a proven path. You will drive AI-assisted development for migration work, including understanding legacy code, generating contracts, adapters, and tests, and keeping parity between old and new. You will partner with Engineering Managers and Product Managers on planning and unblocking cross-team work. You will mentor senior engineers on architecture, system design, and pragmatic decision-making, and 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
- Experience taking large legacy systems apart while they kept serving real traffic; hands-on knowledge of strangler pattern, anti-corruption layers, data migration, and dual-write pitfalls
- 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 points:
- Experience with two-sided marketplaces, search and discovery, or booking and scheduling systems
- Experience with monorepos at scale: build tooling, code ownership, shared platform conventions
- Exposed product capabilities to AI agents
- Healthcare or other regulated domain experience, where data privacy and security shape architecture