Senior Backend Engineer, Ambient AI

The role

You will design, build, and operate backend systems for an ambient AI platform. This includes managing audio processing lifecycles, inference workflows, and orchestration systems for clinical outputs.

What you will do

• Design, build, and operate backend systems for Ambient AI products.
• Own the audio processing lifecycle including ingestion, validation, and storage.
• Build and evolve inference workflows for transcription, diarization, and AI capabilities.
• Develop orchestration systems for long-running, multi-stage workflows.
• Improve reliability and scalability of services under variable workloads.
• Define and maintain service-level objectives for critical workflows.
• Build observability through logging, metrics, tracing, and dashboards.
• Lead incident response and post-incident analysis.
• Improve cloud infrastructure, deployment systems, and capacity planning.
• Design APIs and data models for mobile, web, and internal systems.

Required qualifications

• 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 distributed-systems concepts such as idempotency, consistency, concurrency, backpressure, retries, failure isolation, and eventual completion.
• Experience operating services in a cloud environment, including deployment, monitoring, scaling, and 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.
• Comfort working across backend, infrastructure, product, and AI systems.
• Ownership mindset and bias for action.

Nice to have

• Experience with audio or video ingestion, streaming media, codecs, transcoding, or media-processing pipelines.
• Experience building speech-to-text, diarization, transcription, or other audio-based machine-learning workflows.
• Experience orchestrating large language models or multi-model inference pipelines in production.
• Familiarity with workflow orchestration systems such as Temporal or similar durable execution platforms.
• Experience with event-streaming and messaging technologies such as Kafka, Pub/Sub, SQS, or similar systems.
• 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 production incident response.
• Familiarity with distributed tracing and observability platforms such as Grafana, OpenTelemetry, Sentry, or similar tools.
• Experience with containers, Kubernetes, infrastructure as code, and cloud-native deployment systems.

About the company

Commure is building the AI Operating System for healthcare. Their platform includes Ambient AI, intelligent Agents, and autonomous RCM processing billions in claims.