Senior Software Engineer

About Wisdom

Wisdom blends industry expertise with advanced technology to make dental practices work better for everyone involved. We believe dentistry is about people, and we exist to make the future of dentistry stronger and more sustainable for dentists, their teams, and the patients they serve. We match administrative teams with expert billers and custom-built technology to take on the heavy lifting of dental billing while maximizing dentists’ time in-office, and their bottom line.

Coming from a fresh $21M Series A round of funding we are looking for exceptional candidates to help us build a category-defining company. Wisdom has employees across the US.

About The Role

The roadmap isn't handed to you here. You'll help write it.

As a Senior Software Engineer at Wisdom, you'll own hard problems end-to-end — from schema design to agentic billing pipelines to the React surfaces that billers and practice operators rely on every day. You'll work on a small, high-trust team where your technical decisions have real consequences, the feedback loop with users is short, and your fingerprints are on the product.

Wisdom's stack is TypeScript, Node.js, React, Postgres, and AWS. The problems we're solving — reliable integrations with inconsistent insurance systems, AI-driven billing decisions that have to be right, HIPAA-compliant infrastructure that can't fail — are legitimately hard. We'd rather have someone energized by that than simply tolerant of it.

In your first year, you'll have shipped core pieces of our agentic billing infrastructure, established deep ownership over at least one major product surface, and helped raise the bar for how this team builds. This is a fully remote role reporting directly to the Head of Engineering.

What You'll Own

Design and ship production-grade features across the full stack — backend services, cloud infrastructure, and user-facing React interfaces

Build and evolve AI-powered agentic workflows that automate complex, high-stakes billing decisions at scale — not prototypes, production systems

Architect resilient integrations with dental insurance carriers and practice management systems (Dentrix, Eaglesoft) — poorly documented, inconsistent, and absolutely critical to get right

• Work directly with dental billers and practice operators to understand problems at ground level, then translate that into software decisions
• Hold a high bar for code quality, reliability, and operational health across the codebase — including code review and technical documentation that actually gets used
• Take on ambiguous, undefined problems and drive them to resolution without waiting for permission or a perfect brief

Who You Are

5+ years shipping production software in environments where reliability and quality had real consequences — not just feature velocity

You've built systems under pressure: integrations that had to stay up, services that had to scale, and code that had to be owned and maintained beyond your tenure

Hands-on production experience with at least one major LLM API — OpenAI, Anthropic (Claude), or Google Vertex AI — including tool use, prompt architecture, structured outputs, and handling model behavior in live systems

• Strong command of TypeScript/JavaScript; familiarity with Python or C# is a plus
• Deep experience with relational databases — schema design, query optimization, and reasoning about data integrity under load
• Cloud infrastructure experience in AWS or GCP, including deploying and operating services at production scale
• You default to ownership and move toward hard problems rather than away from them
• You're direct, intellectually honest, and collaborative — you surface bad news early, change your mind when the evidence warrants it, and make the people around you sharper
• You'll Stand Out If You Have
• Experience with the Mastra agent framework or comparable orchestration tools (LangChain, LlamaIndex, CrewAI)
• Working knowledge of HIPAA compliance and what it means to build software responsibly in a healthcare context
• Experience at a Series A or early-stage startup where high autonomy and undefined problems were the norm, not the exception