Note: The job is a remote job and is open to candidates in USA. Ellipsis Health is hiring a Senior Backend Engineer for its AI Evaluation team. The role builds and maintains infrastructure, evaluation frameworks, and debugging tools that help internal teams test, monitor, and operate AI systems reliably at scale.
Responsibilities
- Build and maintain infrastructure and tooling for the AI evaluations platform used by internal teams, including automated testing platform for AI voice agents, debugging and observability tools
- Develop and productionalize evaluation frameworks for individual system components such as ASR, LLMs, TTS, knowledge bases, and guardrails
- Partner with ML, engineering and QA teams to translate evaluation requirements into robust, maintainable infrastructure and tooling
- Improve developer experience by making evaluation systems easy to extend, well-documented, and reliable in day-to-day use
- Ensure evaluation tooling meets production standards for reliability, performance, and maintainability
Skills
- 5+ years of professional software engineering experience, with a strong focus on building backend systems, platforms, or developer tooling
- Proven experience designing and maintaining production-grade infrastructure with code, including APIs, services, and data pipelines
- Strong proficiency in at least one general-purpose programming language (e.g., Python, Typescript/Javascript, Java, or similar)
- Experience using test automation frameworks, evaluation pipelines, or CI/CD-integrated testing systems
- Familiarity with observability and debugging tools (logging, metrics, tracing) and building internal tools that improve developer and QA workflows
- Strong debugging skills and a methodical approach to diagnosing production and evaluation issues
- Ability to collaborate effectively across engineering, QA, and operations teams, translating requirements into reliable, maintainable systems
- Product-minded approach to infrastructure, with attention to usability, documentation, and long-term maintainability
- Experience working with complex, multi-component systems (e.g., ASR, LLMs, TTS, or other ML-powered services)
- Experience working in healthcare or other regulated environments, including awareness of HIPAA and PHI handling
- Familiarity with conversational AI or voice agents, including multi-turn dialogue, latency constraints, and error recovery
- Familiarity with LLM observability or evaluation tools (e.g., Langfuse, prompt eval frameworks)
- Background in digital health, care coordination, or patient-facing systems
Benefits
- 401(k) matching
- Health insurance
- Vision insurance
- Dental insurance
- Very flexible paid time off
- Hybrid work arrangement in San Francisco
Company Overview
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