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# Senior Backend Engineer (Python)

- **Company:** Ellipsis Health, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Information Engineering, Data Stores, Python (Programming Language), PostgreSQL, Public Switched Telephone Networks, Queueing Systems, Redis, Data Streaming, Twilio, WebSocket, WebRTC, Flexi (Photoshop Plugin), Large Language Models, Concurrency, Backend, Agentic-AI, Fastapi, Kubernetes, Low Latency, Apache Kafka, OPUS (Software), Amazon Simple Queue Service (SQS), Terraform, Data Pipelines, Dynatrace, Microservices
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25197_8fb54d6f0adab9cba81c6701b36e4be1

## About the Role

* 4+ years building production back-ends in modern Python.
 * Proven experience with real-time streaming systems-WebRTC, WebSockets, or gRPC streaming-and proficiency with asyncio, FastAPI, or similar async frameworks.
 * Deep understanding of concurrency, buffering, audio codecs (Opus, PCM), and distributed tracing.
 * Solid understanding of AWS/GCP/Azure, including container orchestration (Kubernetes/EKS/GKE), message queues (Kafka/SQS/Pub/Sub), and IaC (Terraform).
 * Solid grasp of relational (PostgreSQL) and in-memory (Redis) data stores; able to model and persist conversational state.
 * Excellent communication skills and a bias for measured, observable, and continuously deployable software., * B.S./M.S. in CS, EE, or related fields.
 * Familiarity with voice-agent frameworks, hands-on with telephony (Twilio, Telnyx), SIP, or PSTN integrations.
 * Experience integrating multimodal inputs (vision, text chat) into voice agents.
 * Familiarity with GPU inference and streaming pipelines.

## Description

* Expand and maintain our real-time voice pipeline: design, implement, and maintain Python micro-services for conversational AI orchestration-audio capture, streaming transcription, prompt/LLM logic, synthesis, and playback.
 * Integrate new providers and transports: add plug-ins for emerging ASR, TTS, LLM, and memory services; wire up WebRTC, SIP, or phone endpoints; build adapters that allow hot-swapping components without downtime.
 * Build APIs to deliver ultra-low latency (500 ms round-trip): profile async pipelines (asyncio, FastAPI, gRPC), optimize buffering, concurrency, and back-pressure handling.
 * Instrument and observe every hop: emit structured traces (OpenTelemetry), metrics, and logs for each pipeline stage; define SLOs for first-token latency, end-to-end latency, and streaming reliability.
 * Ensure system resilience and HIPAA-compliant security: implement circuit breakers, encryption in transit, per-tenant isolation, and secrets rotation.
 * Collaborate cross-functionally with ML, product, data engineering, and client-SDK teams to deliver features such as voice cloning, multimodal hand-offs, and domain-specific memory retrieval.