QA Engineer - Voice AI (Vietnamese Language)

Neurons Lab.com

Vietnam Remote part_time

Posted: January 20, 2026

Job Description

About the project

This project delivers a Vietnamese Voice AI PoC that automates high-volume outbound telemarketing calls using real-time voice interaction and LLM-based intent handling. The solution improves call consistency and conversion quality, benchmarks multiple ASR/TTS providers in Vietnamese, and enables safe human handoff for complex cases. The PoC provides ILA with clear performance metrics and a scalable foundation for expanding voice automation without linear cost growth.

Duration: 3-5 weeks

KPI

KR1: ≥95% test coverage for top telemarketing scenarios and top 20 intents

KR2: 0 P0 / P1 defects open at PoC demo and readout

KR3: Human handoff triggers correctly in ≥99% of low-confidence or edge cases

KR4: Consent / opt-out / fallback flows pass 100% of compliance test cases

KR5: Escalation and hang-up logic validated across all supported call paths

Areas of Responsibility

• Define and maintain QA strategy for Voice AI PoC → MVP

• Design test scenarios for telemarketing flows, intents, and edge cases

• Validate ASR/TTS quality (WER/CER, accent robustness, noise conditions)

• Test LLM intent accuracy, fallback behavior, and confidence thresholds

• Verify human handoff, consent, DNC, and compliance-related logic

• Analyze QA metrics and provide go/no-go recommendations

• Ensure demo and readout readiness (no surprises on demo day)

Skills

• QA for voice, conversational AI, or IVR systems (Vietnamese language)

• Scenario-based and exploratory testing

• Experience with API, backend, and integration testing

• Log analysis, trace inspection, and defect root-cause analysis

• Ability to translate business flows into testable acceptance criteria

Knowledge

• Voice AI fundamentals: ASR, TTS, WER, CER, latency metrics

• LLM-based intent detection and confidence thresholds

• Call flow logic: barge-in, interruptions, silence handling, hang-ups

• Telemarketing and contact-center workflows (nice to have)

• QA metrics and release readiness criteria

• Basic understanding of compliance concepts (consent, opt-out, escalation)

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