Senior QA Automation Engineer (AI)

• →Coordinate QA activities across all Neio Project products.
• →Own QA planning, work allocation, test execution tracking, and status reporting.
• →Guide the 3–5 years QA resources on test coverage, automation standards, and defect quality.
• →Review test cases, automation scripts, API test coverage, and execution results.
• →Act as the primary QA point of contact for product, development, and business teams.
• →Ensure timely QA sign-off inputs for releases.
• →Drive automation framework improvements and QA process consistency.
• →Track QA metrics such as test execution progress, defect status, automation coverage, and regression results.
• →Identify testing risks early and escalate blockers to stakeholders.

• Experience testing AI/ML-based applications, chatbots, RAG platforms, LLM-based tools, or document processing systems.
• Knowledge of chatbot testing, prompt validation, AI response quality checks, hallucination checks, and fallback response validation.
• Experience with OCR, document extraction, document synthesis, summarization, or NLP-based products.
• Experience with database validation using SQL.
• Exposure to performance testing tools such as JMeter or k6.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with accessibility, security, or compliance testing.

The ideal candidate should be a hands-on QA automation professional with strong experience in both UI and API testing. The candidate should be able to understand business requirements, create effective test scenarios, perform functional testing, and automate stable regression flows using Selenium or Playwright.

The candidate should have practical experience in API validation using Postman and API automation using Rest Assured with a framework-based approach. They should be comfortable working in an Agile environment, collaborating with developers, product owners, business stakeholders, and AI teams.

Since the Neio Project includes AI-driven products such as Neio AI Chat Bot, RAG Platform, document extraction, document synthesis, and generated letter workflows, the candidate should be open to validating AI outputs for accuracy, consistency, relevance, and business correctness.

For the senior QA profile, the candidate should additionally have the ability to coordinate work across multiple products, guide junior and mid-level QA resources, review QA deliverables, track progress, and represent QA status to stakeholders.