Staff Software Engineer (Distributed Systems)

Ambience processes millions of patient encounters across the nation’s largest health systems

These organizations trust us with real-time clinical workflows where latency and reliability directly impact patient care

A slow response during a patient visit isn’t just a bad metric; it’s a physician abandoning the tool

You’ll own the core systems that let Ambience scale reliably: database architecture, caching, multi-tenancy, and the performance optimization that determines whether our products feel fast or frustrating to clinicians

You’ll design database architecture that handles our growth trajectory, build caching systems that keep EHR API latency out of critical paths, and create multi-tenant infrastructure that isolates customer data without sacrificing performance

The goal: infrastructure that other teams depend on without thinking about it

Database Architecture & Scaling — Own database performance end-to-end: query optimization, indexing strategy, connection management, capacity planning. Design multi-tenant data patterns that maintain performance while balancing isolation tradeoffs

Caching & Latency Optimization — Build caching infrastructure that keeps EHR API latency out of critical user paths. Identify and optimize hot paths across the application. Build instrumentation to catch performance regressions before they reach users

Rate Limiting — Design systems that respect EHR API rate limits while maintaining user experience. Build infrastructure that degrades gracefully under load: queue management, circuit breakers, load shedding

Reliability & Observability — Dashboards and alerting for database performance, cache hit rates, connection pool utilization, API latency by customer. Systematically identify and harden against failure modes: connection exhaustion, cache stampedes, thundering herds

Strong backend fundamentals in Python, Go, TypeScript, or similar

7+ years in software engineering, 3+ focused on infrastructure, backend systems, or platform engineering

Comfort reading code across the stack to trace performance issues

Deep experience with relational databases (Postgres preferred)

Track record of diagnosing and solving scaling or reliability problems

Staff-level scope: owned cross-cutting infrastructure, debugged production issues that stumped others