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Commure is building an AI Operating System for healthcare that spans the full care journey: Ambient AI and Dictation eliminating documentation burden, intelligent Agents automating patient and revenue workflows, and autonomous RCM processing billions in claims. The company serves 500,000+ clinicians across 500+ healthcare organizations, handles $25B+ in annual claims, and recently raised $70M at a $7B valuation.
You will design, build, and operate backend systems powering Commure's Ambient AI products. The role focuses on building a distributed system responsible for ingesting long-form audio, processing real-time and asynchronous streams, orchestrating multiple AI models, and reliably producing clinical outputs. You'll work across audio ingestion, media processing, inference orchestration, distributed workflows, storage, observability, and cloud infrastructure.
Key responsibilities include:
- Design and operate backend systems for Ambient AI products across mobile and web
- Build inference workflows coordinating transcription, diarization, language models, clinical extraction, and summarization
- Develop orchestration systems for long-running, multi-stage workflows with scheduling, queueing, retries, idempotency, and graceful degradation
- Improve reliability and scalability of services under variable, compute-intensive workloads
- Define and maintain SLOs for critical workflows including availability, latency, completion rates, and data durability
- Build strong observability through structured logging, metrics, distributed tracing, dashboards, and alerting
- Lead incident response and post-incident analysis for production failures
- Identify and eliminate systemic failure patterns through better abstractions and architecture
- Improve cloud infrastructure, deployment systems, and operational tooling
- Design APIs and data models for safe interaction with long-running workflows
- Build tools for inspecting, testing, replaying, and debugging inference pipelines
- Balance reliability, latency, quality, and cost across AI and media-processing workloads
- Partner with mobile, product, AI, security, and clinical teams
- Mentor other engineers on distributed systems and backend architecture
Requirements:
- 8+ 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 distributed-systems concepts: idempotency, consistency, concurrency, backpressure, retries, failure isolation, eventual completion
- Experience operating services in cloud environments: deployment, monitoring, scaling, incident response
- Experience designing APIs, service boundaries, and data models for complex product workflows
- Track record of improving system reliability, observability, scalability, or operational efficiency
- Strong debugging skills across application, infrastructure, data, and external dependency boundaries
- Ability to reason about both real-time and long-running workloads with different latency and durability requirements
- Comfort working across backend, infrastructure, product, and AI systems
- Ownership mindset and bias for action
Nice to haves:
- Experience with speech-to-text, diarization, transcription, or audio-based ML workflows
- Experience orchestrating LLMs or multi-model inference pipelines in production
- Familiarity with workflow orchestration systems like Temporal
- Experience with event-streaming technologies: Kafka, Pub/Sub, SQS
- Experience with model routing, inference gateways, rate limiting, batching, caching, or GPU-backed workloads
- Experience building internal tooling for workflow inspection, replay, evaluation, or model debugging
- Experience defining SLOs, managing error budgets, designing alerts, and leading incident response
- Familiarity with distributed tracing and observability platforms: Grafana, OpenTelemetry, Sentry
- Experience with containers, Kubernetes, infrastructure as code, and cloud-native deployment
- Experience optimizing for throughput, tail latency, infrastructure cost, and workload isolation
- Experience with offline clients, background synchronization, or systems reconciling delayed/duplicated events
- Exposure to healthcare, HIPAA, SOC 2, encryption, privacy, security, or regulated environments
- Experience supporting AI-native, real-time, or agentic product experiences
