Staff Software Engineer, Distributed Systems

present of AI; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Ambience Healthcare seeks a Staff Software Engineer to own the distributed infrastructure for its clinical documentation product in San Francisco. You will design scalable databases, implement caching to keep external calls fast, and apply rate limiting with strong observability.

The role emphasizes multi-tenant performance, tracing across the stack, and secure data handling under compliance constraints. AI-driven workloads demand fast, dependable systems and robust degradation strategies.

Qualifications

• Years of backend and platform experience.
• Deep relational database skills.
• Proven track record in production scale and reliability.

Responsibilities

• Own the shared infrastructure behind the clinical documentation product.
• Design and scale databases; implement caching to reduce external API calls.
• Apply rate limiting and observability to maintain reliability.
• Trace performance across the stack and improve multi-tenant systems.

Skills

Backend engineering

Platform experience

Relational databases

Performance tracing

Caching

Observability

Tools

PostgreSQL

Redis

Load testing

Job description

Staff Software Engineer, Distributed Systems

Engineering · San Francisco · FullTime · Senior level

This role owns the shared infrastructure behind a clinical documentation product: database design and scaling, caching to keep external health record calls off the critical path, rate limiting, and observability. A strong candidate has years of backend and platform work, deep relational database skill, and a record of fixing production scaling and reliability problems that others could not. The work is cross cutting, so comfort tracing performance issues through code across the stack matters more than any single language.

How it fits the AI era

The product turns live clinical conversations into documentation, coding and checks, so the systems underneath must stay fast and dependable while that processing runs. AI raises the volume and variability of traffic, which makes caching, queueing and graceful degradation more important, not less. Judgment about data isolation, retention and access controls stays human, as does deciding which tradeoffs are acceptable when patient care workflows depend on the result.

How it builds AI experience

Working here means building the plumbing that carries AI generated clinical output at scale, so the AI learning comes from seeing how model driven features behave under real load and real latency limits. Candidates can prepare by studying how caching and rate limiting interact with external APIs, and by practicing performance tracing on multi tenant systems. Familiarity with handling sensitive data under compliance constraints would help, since patient information flows through these paths.

Worth showing

• Database scaling and query tuning
• Caching and latency reduction
• Reliability and observability tooling

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Ambience Healthcare

AI that listens to clinical visits and drafts the documentation, coding and clinical checks so doctors spend less time on the screen.