Job Title: SDET (Software Development Engineer in Testing) – Senior Automation QA & Manual Testing
Experience: 8+ Years
Employment Type: Full-Time
Dept: FSD
Designation: Senior Specialist – FSD QA
Location: Hybrid
About Us
At InxiteOut Pvt. Ltd., we specialize in building next-generation AI-powered applications that solve real-world business problems. We are expanding our QA team to ensure our AI systems are robust, secure, and aligned with user expectations.
Key Responsibilities
· Strong knowledge of Python.
· Configure and test AI/ML product/system.
· Lead the quality assurance strategy and establish automation frameworks from scratch.
· Manage and mentor junior QA engineers and guide them in test automation and AI system validation.
· Own functional and non-functional testing across complex distributed systems.
· Own API, integration, acceptance, system, and end-to-end (E2E) testing.
· Lead test planning, test case design, and execution for web, API, and AI-based systems.
· Design and maintain regression test suites and ensure full coverage.
· Collaborate with Full Stack Developers, Data Scientists, and AI Engineers to define test strategies for LLM-based features.
· Own testing of AI-specific behaviors including:
o Hallucination and factual accuracy
o Consistency in prompt-response pairs
o Retrieval-Augmented Generation (RAG) flows
· Collaborate with developers, product owners, and other QA engineers in Agile teams.
Must-Have Skills
· Deep experience in Functional Testing:
o Advanced REST API Testing (Postman, REST Assured, etc.)
o Integration, Acceptance, E2E, Smoke, Sanity, System Testing
· Strong foundation in Non-Functional Testing:
o Performance and Load Testing
o Stress and Security Testing
· Proficiency in Testing Methods:
o Black-box, White-box, Grey-box Testing
· Regression Testing lifecycle ownership
· Expertise in automation frameworks (e.g., Selenium, Playwright, Cypress, TestNG)
· Strong scripting/coding skills in Python (preferable) / Java / JavaScript
· Familiarity with containerized environments (Docker, Kubernetes)
Good-to-Have (AI Testing Focus)
· Exposure to testing AI/ML products/systems.
· Experience of integrating tests into CI/CD pipelines (GitHub Actions, GitLab, Azure DevOps etc.).
· Hands-on experience with AI testing tools or custom frameworks.
· Familiarity with evaluating LLM (large language model) outputs.
· Experience of validating RAG-based architecture.
· Understanding of hallucination detection metrics and prompt tuning.
· Exposure to safety audits for AI applications.
· Collaboration experience with Full Stack, Data Science, Data Engineering & DevOps teams.
Qualifications
· Bachelor’s or master’s in computer science, Engineering, or related field.
· Certifications in testing or security are a plus (e.g., ISTQB, OWASP).