PracticeMatch is the market leader in physician recruiting data. Hospitals and health systems across the US use it to find and reach physicians, and physicians use it to find their next role. We're profitable, two decades in, and backed by M3, a Nikkei 225 healthcare company with more than $1 billion in annual revenue. We're rebuilding PracticeMatch a piece at a time while it serves customers every day. We want a technically deep engineering leader who still builds, has modernized a live system before, and thinks AI has made this an unusually good moment to do it again. At a glance You report to the PracticeMatch CEO, who also leads M3 USA. You lead the PracticeMatch engineering and QA team. You move us from ColdFusion, SQL Server to TypeScript and Python in the cloud, incrementally. No big-bang rewrite. You're hands-on: in the code every week, writing it, reviewing it and designing it. Fully remote in the US. What you're walking into Years of business logic live in stored procedures across roughly SQL Server databases, behind a ColdFusion application customers use every day. It is large, interconnected and it works, which is exactly why it has to change carefully. The team knows the platform, the data and the customers deeply. Your job isn't to replace that knowledge. It's to give the team better architecture, better tools and better ways to build. The Head of Product sets the product roadmap, grounded in direct customer evidence. Engineering work goes on that same roadmap, with real people assigned to it, whenever it serves a business outcome: shipping faster, fewer production bugs, less outage risk, or meeting the security and compliance bar that opens new customers. What's decided, and what's yours Decided. Whether to modernize is settled. We do it incrementally, and every step has to work in production. The target languages are TypeScript and Python, M3 USA's standard, chosen for type safety and readability. Cloud will be AWS or Azure, picked on cost and benefit. Physician search moves to Elasticsearch or OpenSearch. Yours. The target architecture. The order of migration, and which pieces get rebuilt alongside which product work. How the team plans, builds, tests and ships. You'll work these out with the team and the Head of Product, and bring any case for an exception to M3 USA's CTO. The job Lead the modernization. Set the architecture and a phased path to it. Build the foundations that make change safe: test automation, CI/CD, observability and the cloud platform. Own production engineering, and when something important breaks, lead the response and fix the cause, not the symptom. Make delivery something the business can plan on. Sales and marketing need to know what's coming next quarter, and you and the Head of Product are measured on that together. Small, frequent releases are how fast and predictable stop pulling against each other. We want honest forecasts, not padded estimates. Make AI part of how the team builds. Shared repository context, conventions, quality gates and review discipline, working toward automation from ticket to pull request. Human review stays wherever it protects quality and compliance. Lead by building. You'll write significant code, do much of the architecture and review most of the rest. You could do everything the team does yourself; the job is to make sure you don't have to. Go first on unfamiliar ground, then bring everyone along at their own pace. Give direct feedback early and hold a high bar without a lot of process. How you'll work Engineering owns how and when; Product owns what and why; you and the Head of Product give leadership one view. You'll work closely with M3 USA's CTO on shared strategy and standards. You report to the CEO, so there is very little distance between a good idea and acting on it. When you think we're wrong, say so. We want a partner, not someone to execute a plan that's already finished. You might be our person if You've taken a live system that was hard to change and made it much easier to change. Asked how, you get specific: boundaries, tests, migrations, cutovers, mistakes. You can show what changed in numbers, and describe where a Product and Engineering partnership broke down and what you did about it. You're technically broad without being hand-wavy. Architecture, databases, infrastructure, CI/CD, testing, observability, security and application code are all familiar ground, and you go deep when the problem needs it. AI is already how you build. You know how useful coding agents are and how confidently wrong they can be. You've worked where the problem didn't stop at the edge of your job description: a startup, an early product, or anywhere you had to build the structure yourself. You have engineering taste. You can tell when an abstraction is earning its keep, and when "temporary" is about to become permanent. You make the people around you better. You teach without showing off and change your mind when the evidence changes. Probably not for you if You want a steady-state platform to keep running smoothly. You'd rather freeze the legacy system while a new team spends two years rewriting it. Your interest in AI lives in strategy decks rather than in building with it. You prefer to lead from a distance, through layers of management and quarterly slides. You want complete autonomy outside any shared strategy. What you don't need ColdFusion experience. It's a small language, and if you can learn enough in a week to read it, that's enough. Healthcare or physician-recruiting experience, though if you've worked with a rich real-world domain model you'll recognize this one. A particular number of years in a particular title: we care what you've done and how you think about it.