Senior QA Engineer, Forward Deployed

Ellipsis Health; United States; Remote; USD 120,000 - 140,000; Full time

Benefits offered by this job

401(k) matching

Health, vision, and dental insurance

Flexible paid time off

Job summary

Ellipsis Health seeks a Forward Deployed QA Engineer to ensure Sage’s reliability across enterprise workflows. You will bridge QA, AI engineering, and Production Operations, focusing on automated testing, prompt validation, and rapid RCA of LLM behaviors in fast-paced deployments.

This role emphasizes designing robust test cases from client workflows, building automated tests with shadow agents, evaluating prompts, and collaborating with engineering during releases to maintain deployment

Qualifications

• QA engineering experience designing, executing, and managing end-to-end test strategies (Smoke, Sanity, Regression, Functional).
• Hands-on troubleshooting of LLM behaviors, hallucinations, latency, and using LLM tracing tools.
• Ability to write SQL queries (PostgreSQL) and navigate cloud logs (GCP) for rapid RCA.
• Foundational knowledge of Speech-to-Speech pipelines, ASR, audio-to-text workflows, and knowledge-base integrations.
• Strong client-facing skills to manage UAT timelines and coordinate with stakeholders.

Responsibilities

• Analyze client workflows to design robust test cases, including positive and negative scenarios.
• Build automated test scenarios by configuring shadow agents and running tests.
• Evaluate prompts to simulate user behaviors and edge cases within the framework.
• Execute end-to-end testing across staging, pre-production, and production environments.
• Collaborate with engineering during releases to identify and unblock roadblocks.
• Perform daily root-cause analysis on LLM-specific failures (hallucinations, latency, logic issues).
• Debug live production calls and incidents to maintain uptime.
• Validate audio transcripts and S2S pipeline performance across the workflow.
• Apply advanced evaluation frameworks to measure AI quality at scale.
• Understand telephony routing, warm/blind transfers, and voicemail detection in real deployments.

Skills

QA Engineering

LLM & Generative AI

SQL (PostgreSQL)

GCP Logging

Voice AI & Telephony

Telephony Concepts

Client-Facing Communications

Tools

PostgreSQL

GCP

Job description

About the Team

The Forward Deployed Team is our primary customer-facing unit, acting as the crucial bridge between our core product and our enterprise clients. This fast-moving team manages the end-to-end lifecycle of enterprise conversational AI deployments, from pre-sales Statements of Work (SOWs) through go-live.

We maintain daily, high-touch interactions with customers to communicate workflow progress, manage User Acceptance Testing (UAT) deadlines, integrate client feedback, and ensure that deployments are executed rapidly while maintaining rigorous quality standards.

Ellipsis Health is located in the San Francisco Bay Area, but we are open to remote candidates within the United States.

About the Role

As a Forward Deployed QA Engineer, you will occupy a critical, high-impact role dedicated to ensuring the reliability, stability, and quality of our core conversational AI product, Sage, across diverse client workflows.

This role bridges the gap between Quality Assurance, AI Engineering, and Production Operations. You will focus heavily on automated testing, prompt engineering validation, and rapid root cause analysis (RCA) of Large Language Model (LLM)-driven behaviors in fast-paced, real-world deployments.

Responsibilities:

• Workflow Mapping & Test Case Generation: Deeply analyze assigned client workflows to design robust, comprehensive positive and negative test cases that safeguard system stability.

• AI-Driven Test Automation: Build and execute automated test scenarios by configuring shadow agents.

• Prompt Evaluation & Optimization: Apply a strong understanding of prompt awareness to draft, refine, and evaluate prompts used within the testing framework to accurately simulate user behaviors and edge cases.

• End-to-End Testing Execution: Strategically deploy specific testing methodologies including Sanity, Smoke, Regression, and Functional testing - determining the exact environment (staging, pre-production, production) and timing for each execution.

• Deployment Cadence & Cross-Functional Collaboration: Partner closely with engineering teams during release cycles to proactively identify, triage, and unblock technical roadblocks, ensuring the product is continuously deployment-ready.

• Daily LLM Defect RCA: Perform rigorous, daily root cause analysis on LLM-specific failures inherent to generative AI, including hallucinations, high latency, and logic deviations.

• Live Production Call Debugging: Investigate live customer calls and production incidents in real time to unblock critical production use cases.

• Audio & Transcription Validation: Query and analyze historical call transcripts, system behaviors, and audio data pipelines to pinpoint where a conversational workflow broke down.Speech-to-Speech (S2S) Pipeline Monitoring: Monitor and evaluate the end-to-end voice AI pipeline. This involves analyzing Automatic Speech Recognition (ASR) accuracy, managing audio-to-text latency issues, and understanding general Speech-to-Speech mechanics alongside the stability of the core Knowledge Base feeding the AI.

• Advanced Evaluation Frameworks: Maintain a strong conceptual understanding of advanced LLM evaluation paradigms and tools such as LLM-as-a-judge - to remain aware of how AI response quality and accuracy are programmatically graded at scale.

• Telephony & Call Flow Awareness: Possess a foundational understanding of real-world call management and telephony routing concepts, including how the system is expected to navigate warm transfers, blind transfers, and voicemail detection workflows.

Qualifications:

• Experience in QA Engineering: Strong background in software quality assurance, with a proven track record of designing, executing, and managing end-to-end test strategies (Smoke, Sanity, Regression, Functional).

• LLM & Generative AI Expertise: Hands-on experience or deep technical familiarity with troubleshooting LLM behaviors, diagnosing hallucinations, managing latency, and using LLM call-tracing tools.

• Technical & Logging Proficiency: Ability to comfortably write SQL queries (specifically PostgreSQL) to pull data logs and navigate cloud infrastructure logs (such as GCP) to perform rapid root-cause analysis.

• Voice & Conversational AI Domain Knowledge: Foundational understanding of Speech-to-Speech pipelines, including Automatic Speech Recognition (ASR), audio-to-text workflows, and core knowledge base integrations.

• Telephony Foundations: Basic familiarity with enterprise telephony routing, call management mechanics (warm/blind transfers), and voicemail detection systems.

• Client-Facing Capability: Strong communication skills and the professional agility required to manage UAT timelines, coordinate with client stakeholders, and support rapid production deployments.

Salary and Benefits

We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off.

The typical salary range for this role is $120,000 to $140,000 USD, depending on skills, qualifications, and relevant experience.

Background Checks

As a health technology company, we reserve the right to run background checks on candidates to whom we extend offers, in compliance with applicable laws. We evaluate candidates holistically and comply with all “ban the box” regulations.

Assistance

If you have a disability or require accommodations during the application or recruitment process, please contact [e-mail].