Quality Assurance Engineer

🔥 15 minutes ago

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Hupo

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🛡️ Insurance

Artificial Intelligence • SaaS • Insurance

Hupo is an AI-first company (founded in 2022) that builds a full-stack, software platform to coach and upskill frontline financial advisors and insurance distributors. Using AI to restore confidence, accelerate learning, and improve sales performance, Hupo targets Wealth & Insurance distribution and sells enterprise-grade coaching and productivity tools designed to reduce early rep churn and accelerate mastery. The company emphasizes remote, high-autonomy culture and positions its product as an AI-powered engine for enterprise clients in financial services and insurance distribution.

📋 Description

• Build and maintain automated testing for AI voice and chat agents, from single conversational turns to full roleplay flows. • Test LLM output quality - correctness, consistency, structured output, language fidelity, prompt regression - using evaluation harnesses (LLM-as-judge, golden datasets, tolerance-based assertions for non-determinism). • Validate RAG pipelines: retrieval relevance, grounding/faithfulness, and answer quality. • Test voice pipelines: STT/TTS accuracy and real-time, low-latency behavior across languages. • Automate across UI/E2E, API, and AI output layers, and build CI/CD from scratch - lint, type-check, tests, evals, coverage gates, deployment checks. • Own release quality: regression strategy, catching breakages early, and clear go/no-go calls. • Cover database and load/performance testing; extend automation to desktop and mobile clients. • Take over and extend existing QA automation, and strengthen shared frameworks, tooling, and QA processes/standards.

🎯 Requirements

• 5+ years as a QA Automation Engineer, with a proven track record testing AI systems - not just traditional software. • Builder mindset: established testing frameworks, standards, and CI/CD-integrated automation from scratch. • Hands-on experience testing conversational AI - voice and/or chat agents - on real, shipped projects. • Strong grasp of LLMs, prompt engineering, and RAG - designing tests for nondeterministic output and evaluating retrieval/generation quality. • Understanding of voice pipelines (speech-to-text, text-to-speech) and how to test them in automation. • Hands-on with LLM evaluation/observability tooling - e.g. Langfuse, LangSmith, DeepEval, RAGAS. • Proficient in UI/E2E (e.g. Playwright) and API test automation; experience building CI/CD pipelines from scratch. • Comfort with database testing, load/performance testing, and desktop/mobile test automation. • Solid Git discipline, basic cloud knowledge, and familiarity with the agile sprint lifecycle. • Track record in fast-paced, fast-shipping environments - ramps quickly on unfamiliar systems, pragmatic about process.

🏖️ Benefits

• Flexible work arrangements