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Senior Backend Engineer, Infrastructure

Ellipsis Health

Company websiteellipsishealth.com (Ellipsis Health, opens in new tab)

Base salary $175K  to $250K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceHybrid
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since

About this job

Ellipsis Health is developing cutting-edge AI/ML products to address healthcare staffing issues and administrative burdens. The platform employs conversational AI and patented vocal biomarker technology to deliver improved healthcare experiences for clients and patients. The team is headquartered in Silicon Valley and is funded and supported by preeminent venture capital groups and healthcare institutions.

Responsibilities:

  • 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 & 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 API

    endpoints.

  • Deliver ultra-low latency (<500 ms round-trip): profile async pipelines (asyncio,

    FastAPI, gRPC), optimize buffering, concurrency, and back-pressure handling.

  • Instrument & 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.

  • Harden for production: implement graceful retries, idempotent message

    passing, circuit breakers, and HIPAA-compliant security (encryption in transit,

    per-tenant isolation, 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.

Qualifications:

  • 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.

    Bonus Points:

  • 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.

  • Prior work in regulated industries (healthcare, finance) and comfort preparing for

  • SOC 2 / HIPAA audits.

Salary and Benefits

We offer competitive salary and benefits, including 401k matching up to a certain

percentage of your salary, health, vision, and dental insurance, and very flexible paid

time off.

The typical salary range for this role is $175,000 to $250,000 USD. The amount

offered will be determined by a variety of factors including but not necessarily limited to

your individual skills, qualifications, and past experience relative to the requirements of

the role.

Background Checks

As a health technology company, we reserve the right to run a background check on

any applicant to which we extend an offer and to re-perform any such check at any time

during the course of employment. Please know that there is no set policy on rejecting

candidates because of certain background check results, and that we look at a

candidate as a whole before making any decisions. We comply with all “ban the box”

laws in applicable jurisdictions.

Assistance

If you have a disability or otherwise require any assistance whatsoever in the

application or recruitment process, please feel free to submit a request to

[email protected].

Source: Ellipsis Health on Ashby · View original posting (opens in new tab)

This range next to 6 other live Ellipsis Health roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Ellipsis Health roles with the nearest advertised base floor
RolePublished base
Senior Backend Engineer, Infrastructure (this listing)$175K - $250K
Senior DevSecOps Engineer$160K - $250K
Senior Director of Marketing$160K - $185K
Senior Backend Engineer, Core Services$160K - $210K
Senior Full Stack Engineer, Core Services$160K - $210K
Senior Data Platform Engineer$150K - $170K
Director of Customer Success$150K - $190K

Same $100K to $400K scale as every card. All Ellipsis Health roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-05-01
Where this pay comes from

Location as the employer wrote it: San Francisco - Hybrid

USD 175,000 – 250,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.