QA Engineer

🔥 12 hours ago

🇮🇳 India – Remote

💵 ₹1M - ₹2.5M / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔧 QA Engineer (Quality Assurance)

👻 Ghost score 20%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 33 days.
• 167 open roles for a team of 134.

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💼 Consulting

👥 HR Tech

☁️ SaaS

Consulting • HR Tech • SaaS

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• Define and implement test plans for GenAI, LLM, Agentic AI, and RAG systems • Design and maintain automated test suites using pytest and Python • Develop and execute API tests for model endpoints, data pipelines, and microservices • Perform functional, regression, and performance testing of AI services • Integrate testing into CI/CD pipelines with tools like Jenkins, GitHub Actions, or GitLab CI • Analyze model output quality, bias, and fairness metrics and document findings • Collaborate with ML teams to create test harnesses for new model releases • Create and maintain test data sets, fixtures, and mock services • Report defects, track resolution, and validate fixes to ensure quality standards • Mentor junior testers and promote best practices in AI QA • Work closely with data scientists, ML engineers, and product managers to validate Agentic AI and RAG workflows • Monitor performance metrics, detect anomalies in generated outputs, and maintain documentation and dashboards • Drive adoption of scalable QA practices across the organization

🎯 Requirements

• 4+ years of QA engineering experience in AI or data science environments • Strong proficiency in pytest, Python, and API testing frameworks (e.g., Requests, RestAssured) • Hands-on experience with GenAI, LLM, Agentic AI, and RAG testing methodologies • Familiarity with CI/CD pipelines and automation tooling (Jenkins, GitHub Actions) • Deep understanding of AI ethics, bias mitigation, and model explainability • Excellent analytical and problem-solving skills with a detail-oriented mindset • Ability to translate complex AI concepts into clear, testable requirements • Strong communication skills for cross-functional collaboration • Proven track record of delivering high-quality releases on time • Passion for staying current with emerging AI technologies and testing trends

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