3 months ago
Base Salary
$170k - $230k/yr
Responsibilities
- Design, build, and operate backend systems powering Ambient AI products across mobile and web.
- Own real-time and asynchronous audio ingestion, streaming uploads, media processing, durable storage, and recovery from interrupted, duplicated, delayed, or out-of-order uploads.
- Build inference workflows coordinating transcription, diarization, language models, clinical extraction, summarization, and other AI capabilities.
- Develop durable multi-stage workflow orchestration with scheduling, queueing, retries, timeouts, fallbacks, dead-letter handling, idempotency, replay, model routing, and progress tracking.
- Improve service reliability and scalability under variable, compute-intensive workloads while balancing latency, quality, and infrastructure cost.
- Define service-level objectives for availability, latency, completion rates, and data durability.
- Build observability through structured logging, metrics, distributed tracing, dashboards, alerting, and diagnostic tooling.
- Lead incident response and post-incident analysis, and eliminate systemic failure patterns through architecture, automation, testing, and operational improvements.
- Improve cloud infrastructure, deployment systems, capacity planning, and operational tooling.
- Design APIs and data models for safe, predictable interaction with long-running workflows.
- Build tools to inspect, test, replay, evaluate, and debug inference pipelines.
- Partner with mobile, product, AI, security, and clinical teams to deliver production-ready workflows.
- Mentor engineers and establish practices for distributed systems, observability, operational readiness, and backend architecture.
Requirements
- 4+ years of professional backend or infrastructure engineering experience.
- Experience designing, building, and operating production distributed systems.
- Strong proficiency in at least one modern backend programming language.
- Experience with asynchronous processing, message queues, event-driven systems, or durable workflow execution.
- Strong understanding of idempotency, consistency, concurrency, backpressure, retries, failure isolation, and eventual completion.
- Experience operating cloud services, including deployment, monitoring, scaling, and incident response.
- Experience designing APIs, service boundaries, and data models for complex product workflows.
- Track record of improving reliability, observability, scalability, or operational efficiency.
- Strong debugging skills across application, infrastructure, data, and external dependency boundaries.
- Ability to reason about real-time and long-running workloads with different latency and durability requirements.
- Comfort working across backend, infrastructure, product, and AI systems.
- Experience with audio or video ingestion, streaming media, codecs, transcoding, or media-processing pipelines is preferred.
- Experience with speech-to-text, diarization, transcription, or audio-based machine-learning workflows is preferred.
- Experience orchestrating large language models or multi-model inference pipelines in production is preferred.
- Familiarity with Temporal or similar durable workflow execution platforms is preferred.
- Experience with Kafka, Pub/Sub, SQS, or similar event-streaming and messaging systems is preferred.
- Experience with model routing, inference gateways, rate limiting, batching, caching, or GPU-backed workloads is preferred.
- Experience with workflow inspection, replay, evaluation, or model-debugging tools is preferred.
- Experience defining SLOs, managing error budgets, designing alerts, and leading incident response is preferred.
- Familiarity with Grafana, OpenTelemetry, Sentry, or similar observability tools is preferred.
- Experience with containers, Kubernetes, infrastructure as code, and cloud-native deployment systems is preferred.
- Experience optimizing throughput, tail latency, infrastructure cost, and workload isolation is preferred.
- Exposure to healthcare, HIPAA, SOC 2, encryption, privacy, security, or other regulated environments is preferred.
- Experience supporting AI-native, real-time, or agentic product experiences is preferred.
Benefits
- Build backend infrastructure for an AI healthcare product used in clinical workflows.
- Solve systems problems involving long-form audio, real-time processing, distributed orchestration, and production AI.
- Work closely with product and AI teams while retaining ownership of backend architecture and infrastructure.
- Help establish operational and engineering standards for a rapidly growing platform.
- Join while core systems, technical strategy, and engineering culture remain highly shapeable.
- Opportunity to grow into broader backend, infrastructure, or technical leadership.
Tech Stack
Categories
About Commure
Commure builds an AI-native healthcare platform for providers and health systems, spanning ambient clinical documentation, provider copilots, coding, and revenue cycle automation, integrated with 60+ EHRs. It sells enterprise software and services to hospitals and care organizations to streamline clinical and administrative workflows. The privately held company is headquartered in Mountain View, California, and reports adoption by 500,000+ clinicians across 500+ organizations, with billions in claims processed annually.