Staff Backend Engineer

NxT Level•San Mateo, CA

About The Position

The Staff Backend Engineer, AI Infrastructure will design, build, and operate distributed systems that power Ambient AI healthcare products across mobile and web applications. The role is hands-on and focuses on reliability, scalability, observability, and orchestration of long-running AI inference workflows, including audio ingestion, transcription, speaker diarization, LLM processing, clinical data extraction, and summarization. The engineer will own critical backend infrastructure and production systems end to end, improve resilience and operational readiness, and balance infrastructure cost, latency, reliability, and model quality. The role also includes technical leadership, mentoring engineers, and establishing standards for distributed systems and operational practices.

Requirements

At least 8 years of backend or infrastructure engineering experience; 7 or more years may be considered for exceptional candidates.
Experience designing, building, and operating production distributed systems at scale.
Strong understanding of asynchronous processing, message queues, and workflow orchestration.
Experience building reliable systems for long-running, compute-intensive workloads.
Strong knowledge of retries, idempotency, timeouts, dead-letter queues, and fault tolerance.
Experience designing production APIs, backend services, and cloud infrastructure.
Deep understanding of observability, monitoring, distributed tracing, and incident response.
Demonstrated ability to improve system reliability, scalability, and performance.
Experience owning production systems end to end, including operational support.
Ability to make architecture decisions in fast-moving, ambiguous environments.
Strong technical leadership and ability to mentor engineers.

Nice To Haves

Current or previous Staff Engineer, Tech Lead, or equivalent technical leadership experience.
Experience building audio, speech, media processing, or real-time streaming infrastructure.
Experience orchestrating multi-stage AI or ML inference pipelines.
Experience with mobile backend systems and unreliable network environments.
Experience building AI applications used in healthcare or clinical settings.
Background combining healthcare technology experience with large-scale engineering at a major technology company.
Familiarity with EHR systems, clinical workflows, or enterprise healthcare infrastructure.

Responsibilities

Design and operate scalable backend systems supporting AI-powered healthcare applications.
Build infrastructure for long-form audio ingestion, media processing, and real-time and asynchronous streaming.
Own orchestration for multi-stage AI inference workflows, including transcription, diarization, LLMs, clinical extraction, and summarization.
Build reliable scheduling, queueing, retries, timeouts, dead-letter handling, idempotency, and replay systems.
Improve system resilience through graceful degradation and recovery mechanisms.
Support mobile and web workflows operating under poor connectivity, unstable networks, and offline conditions.
Define and maintain service-level objectives (SLOs) for critical production workflows.
Build observability through structured logging, metrics, distributed tracing, dashboards, and alerting.
Lead incident response, root-cause analysis, and long-term reliability improvements.
Design and improve APIs, data models, cloud infrastructure, and deployment systems.
Balance infrastructure cost, latency, reliability, and model quality.
Mentor other engineers and establish standards for distributed systems and operational readiness.