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Docplanner is building an AI-native healthcare journey across Marketplace, Patient Engagement and Payments, serving hundreds of millions of interactions.
As Engineering Director you will own the strategy and roadmap for all three areas, shaping AI-enabled discovery, booking, engagement and payments.
You will lead a large, high-trust engineering team, partner with Product and Design, and set standards for AI output, security and quality across 13 markets.
Every month, around 100 million people come to Docplanner to find a doctor, book a visit, stay in touch with their care and pay for it. Each of those steps is now being reinvented with AI.
Search is turning into conversation. Booking is becoming something an agent can do for you. Payments that once needed a human to step in are starting to resolve themselves. Ongoing care is moving from reminders to proactive, personal follow-up.
We’re looking for an Engineering Director to lead that change across Marketplace, Patient Engagement and Payments . It's the part of Docplanner that most patients see and much of what providers depend on. You'll lead around 75 engineers and turn three strong areas into one connected, intelligent patient experience.
Our mission is to help people live longer, healthier lives. We use AI to do that in a way that patients and doctors can trust.
Most engineering leaders are still deciding what AI means for their teams. Here, you get to answer that question at a real scale, in a regulated domain where quality, privacy and trust come first.
You’ll shape two things at once:
What we build: AI-powered discovery, booking, engagement and payment experiences for patients and providers in 13 markets.
How we build it: an engineering organisation where AI-assisted development is simply how work gets done, from writing code to testing and review, with the discipline to know when it helps and when it doesn't.
Set the direction. Own the engineering strategy and roadmap across all three areas. Tie technical bets to product outcomes and to numbers that move.
Build product builders. Build a strong engineering team that thinks in terms of value. Make ownership clear, strengthen the leadership bench and give teams room to decide without waiting on each other.
Turn AI into a product. Work with Product and Design from discovery through delivery to bring AI into search, booking, engagement, continuity of care and payments, where it solves real patient and provider problems.
Continue rewiring how engineering works. We already made a transformation in terms of AI-assisted development across coding, testing and review. We want to go further and need you to set the standards for checking AI output and protecting quality, security and privacy, so moving faster never means being careless.
Own the architecture. Guide design and engineering standards across the portfolio, balancing pace with reliability, security, privacy and scale across markets.
Remove friction at its source. Improve how ideas become impact with clear priorities, a few useful measures and regular learning. Fix recurring problems at the root and keep the process light.
Shape company-wide tech. Align with engineering peers on shared platforms, explain trade-offs to executives and help make technology decisions across Docplanner.
You are hands‑on. This isn't a role where you lead from slides. You use AI coding tools yourself, take part in design and code reviews, and quickly prototype solutions when it helps unblock a hard problem. That technical credibility supports your leadership, while most of your impact comes through the people you develop.
Marketplace, Patient Engagement and Payments work to share priorities and one engineering direction tied to product strategy.
AI features live in the patient journey , and product data shows where they help patients and providers.
AI‑assisted engineering is the default where it adds value , and teams measure what it does for speed, quality and developer experience.
Engineering managers have clear ownership and the tools to lead delivery, people growth and technical decisions on their own.
A small set of useful delivery and quality metrics shows where the bottlenecks are and drives better reliability.
You’ll work on real problems for real people: 100 million patients a month and more than 300,000 doctors who depend on what you ship. You'll do it at a company that t