Staff Software Engineer, Infrastructure

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, then build the parts that matter most. As a Staff Software Engineer at Wisdom, you'll set technical direction across the platform and build the systems that automate dental insurance billing end to end: the LLM-driven agents that make high-stakes billing decisions, the integrations that keep inconsistent insurance and practice-management systems talking to us, the product our customers use every day, and the infrastructure it all runs on. This is a force-multiplier role on a small, high-trust team. You'll go where the hardest, highest-leverage problem is, whether that's a gnarly product feature, a brittle carrier integration, an AI pipeline that needs to fail safe instead of loud, or the deploy path the whole team depends on, and you'll leave both the codebase and the team better than you found them. Wisdom's stack is TypeScript, Node.js, React, Postgres, and AWS, with LLM-driven agents (Mastra, Anthropic) making high-stakes billing decisions in production. The problems we're solving are legitimately hard: keeping inconsistent insurance integrations alive, making AI pipelines fail safe instead of failing loud, and running HIPAA-compliant systems that genuinely can't go down. We'd rather have someone energized by owning problems end to end than someone who wants a narrow lane and a perfect brief. In your first year, you'll have shipped platform-defining work across the stack, raised the technical bar through the code and standards you set, and become the person the team routes its hardest problems to. This is a fully remote role reporting directly to the Head of Engineering. WHAT YOU'LL OWN - Set technical direction across the platform: the architecture, the standards, and the roadmap for systems that bill real money for real practices, plus the judgment about what to build, what to buy, and what to leave alone.

• Build across the whole stack: ship product features, backend services, and the data layer end to end.

• Own how we build and operate AI-powered agentic workflows: the pipelines where LLMs make billing decisions in production, including retries, idempotency, graceful degradation, and cost and capacity controls. The failure modes here are new (batch blowups, stream drops, runaway cost, model misbehavior), and you'll set the patterns the team builds against.
• Harden the integration surface with dental insurance carriers and practice-management systems (Dentrix, Eaglesoft): poorly documented, inconsistent, and the first thing to buckle under load.
• Keep production healthy: fast, safe, reversible deploys, observability that surfaces problems before users do, and an incident practice that runs without heroics.

• Raise the bar through others: set technical standards via code review, architecture guidance, and documentation that actually gets used, and level up how the whole engineering team reasons about building and operating software.
• Take on the ambiguous, undefined, company-level problems and drive them to resolution without waiting for permission or a perfect brief.

• You've shipped across the stack: product features, backend services, and the infrastructure underneath, and you can reason from first principles when the runbook runs out.
• You multiply the people around you.

• Strong command of TypeScript/JavaScript, across both application code and the systems around it. You can go deep wherever the problem is.
• Deep AWS (or GCP) experience.

• Deep experience with relational databases: connection management, query performance, and reasoning about data integrity under load.
• Hands-on production experience with at least one major LLM API (OpenAI, Anthropic (Claude), or Google Vertex AI), with a feel for the operational reality: rate limits, retries, latency, cost, and what happens when the model misbehaves in a live system.
• You default to ownership and move toward the hard problem, not away from it.
• You're direct, intellectually honest, and collaborative.

• Comfort with infrastructure as code (Terraform), containers (ECS/Kubernetes), and CI/CD.

• Working knowledge of HIPAA compliance and what it means to build responsibly in a healthcare context.
• Experience at a Series A or early-stage startup where you built things from scratch rather than inheriting them. Wisdom is an equal opportunity employer.

• Showcase concrete examples of end‑to‑end systems you built, especially any that handled financial or health‑related data.
• Highlight your experience with LLM or AI pipelines; be ready to discuss safety mechanisms you implemented.
• Prepare a brief architecture diagram of a past project that involved complex integrations or multi‑service deployments.
• Emphasize remote‑work discipline: mention tools you use for async communication and how you stay aligned across time zones.
• During interviews, ask specific questions about the current billing pipeline’s failure modes to demonstrate genuine curiosity.
• If offered equity, research Wisdom’s recent Series A round to gauge potential upside before negotiating.
• Watch for any red flag that the team expects you to work without clear specifications; be prepared to negotiate scope clarity if needed.