Raydar
Staff Backend Engineer
$250K–$300K
Mountain View, California · Staff · Full-time · Posted Oct 12, 2026
- Experience
- 7–15 years; typically 8+ years, with exceptional candidates considered from 7 years.
- Education
- Computer Science or other technical degree from a top-30 school, or mid-tier schooling supported by top-tier professional experience.
- Visa sponsorship
- Existing visa transfers may be considered; new visa sponsorship is not available.
About the job
Own and guide the backend distributed systems and reliability that power ambient AI workflows for clinical documentation across mobile and web.
What you'll do
- Build and operate backend systems for long-form audio ingestion, media processing, and real-time and asynchronous streams.
- Orchestrate transcription, diarization, LLM, clinical extraction, and summarization workflows; improve reliability, observability, and incident response.
- Set technical direction, evolve APIs and infrastructure, and mentor engineers while partnering across mobile, product, AI, security, and clinical teams.
What they ask for
- 7–15 years of backend, platform, or infrastructure engineering experience; typically 8+ years, with exceptional candidates considered from 7 years.
- Current Staff Engineer or Tech Lead title, with ownership of technical direction, hands-on delivery, and cross-functional alignment.
- Production distributed-systems experience at scale and strong Python skills or proficiency in a modern backend language.
- Technical degree from a top-30 school, or mid-tier schooling supported by top-tier professional experience.
Nice to have
- Audio, speech, dictation, or real-time media streaming experience; healthcare technology, Epic, HIPAA, or SOC 2 experience.
- Experience with Temporal, Kafka, Google Cloud Pub/Sub, SQS, Kubernetes, infrastructure as code, OpenTelemetry, Grafana, Sentry, or LLM/multimodel inference workflows.
Pay
$250,000-$300,000 annual base salary (USD)
Tools
Python, Temporal, Kafka, Google Cloud Pub/Sub, SQS, Kubernetes, OpenTelemetry, Grafana
AI focus
Orchestrate LLM and multimodel inference workflows, including transcription, diarization, clinical extraction, and summarization.
Model-written summary · the original posting is authoritative