Live opening · Posted 7 hours ago

Quality Assurance Engineer

Scoutit · India (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 7 hours ago
CompanyScoutit
LocationIndia (Remote)
Work modeYes
SkillsJavaScript, TypeScript, React, GraphQL, AWS, Azure, GCP
SourceLinkedin
ListedPosted 7 hours ago

About the role

Description supplied by the original job listing.

We're looking for Quality Assurance Engineers!
Responsibilities:
Perform end-to-end QA on the Nexoar platform, including AI-powered features
Review requirements, user stories, and models/logic to identify risks and edge cases
Create and maintain clear test plans, test cases, and test documentation
Execute manual testing (smoke, regression, exploratory) across releases
Validate AI outputs for accuracy, consistency, bias, and edge conditions
Identify, log, and track bugs with clear reproduction steps and expected behavior
Collaborate closely with developers and product managers to debug issues
Contribute to designing and building QA automation frameworks for Nexoar
Write and maintain automated tests for critical user flows, APIs, and AI pipelines
Help integrate automated tests into CI/CD pipelines
Improve QA processes, tools, and best practices as the product and AI capabilities scale
Advocate for quality, reliability, and responsible AI usage in product decisions
Skills Required:
Frontend: Modern JavaScript framework (e.g., React)
Backend: API-driven architecture (REST / GraphQL)
Databases: SQL / NoSQL
AI/ML: AI-driven features, model integrations, or LLM-based services
Infrastructure: Cloud-based (AWS / GCP / Azure)
CI/CD: Git-based workflows with automated deployments
QA Tools: Jira (or similar), Postman, browser dev tools
Automation: Playwright / Cypress / Selenium (flexible)
Strong manual testing skills with modern web platforms
Experience testing APIs and backend services
Hands-on experience with test automation tools
Comfortable writing automated tests (JavaScript, TypeScript, or similar)
Experience testing AI-driven features (LLMs, ML models, or AI APIs)
Understanding of AI testing challenges (non-determinism, data quality, edge cases)
Experience working in Agile / startup environments
Strong ownership mindset and attention to detail
(Note: Relevant applicants will receive an email requesting additional information as part of the next stage. The application process will be completed directly on the team's designated platform, and all subsequent communication and decisions regarding the opportunity are managed by the respective hiring team.)

Work arrangement
Yes

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