---Advertisement---

🚨AI Quality Engineer Hiring | 5–9 Years | Remote | Immediate Joiners | LLM & Generative AI Testing πŸ€–

By: Rohit BARAHATE

On: August 8, 2026

---Advertisement---
Image

Are you an experienced QA professional who has moved beyond traditional web and API testing and worked directly with AI, LLM, Generative AI or Conversational AI applications? A new AI Quality Engineer opportunity is open for professionals with 5–9 years of experience, strong automation skills and genuine hands-on AI testing experience.

This is not a conventional QA automation position. The requirement specifically emphasizes professionals who have tested AI-powered applications rather than simply using tools such as ChatGPT or Copilot during regular software development projects.

πŸ“Œ Role: AI Quality Engineer
πŸ’Ό Experience: 5–9 Years
🌍 Work Mode: Remote
⚑ Notice Period: Immediate Joiners Only
πŸ€– Focus: AI/LLM/Generative AI/Conversational AI Testing
πŸ“§ Apply: sonali.shraiya@programming.com


🏒 About the Company

The employer is not identified in the vacancy shared, so candidates should verify the company name, official website and employment details with the recruiter before proceeding.

This means the successful candidate is likely to work at the intersection of Quality Engineering, AI evaluation, automation, API testing and software engineering.


🌟 Why Is This Role Good for Experienced QA Engineers?

That creates an exciting career path for experienced QA professionals.

In this role, you could gain practical experience in:

πŸ€– LLM and Generative AI testing
πŸ’¬ Conversational AI validation
🧠 Prompt and model regression testing
πŸ”— AI-agent workflow testing
πŸ› οΈ Tool-calling validation
πŸ“Š AI evaluation datasets
βš™οΈ Automation framework development
πŸ”Œ API and backend testing
πŸ”„ End-to-end AI workflow validation


πŸ› οΈ Skills Required

Candidates should have strong traditional QA fundamentals combined with AI-testing knowledge.

AI Testing: LLM testing, Generative AI testing, chatbot testing, conversational AI, prompt testing and response evaluation.

Conversational Testing: Intent recognition, intent routing, context retention, multi-turn conversations, fallback scenarios and escalation workflows.

AI Evaluation: Relevance, correctness, groundedness, hallucination detection, response consistency and model regression.

Agent Testing: Tool calling, workflow orchestration, agent-to-agent interactions and failure handling.

Automation: Playwright, Selenium or Cypress.

Programming: Python, JavaScript, Java or C#.

API: Postman, REST APIs, authentication, request/response validation and backend integration.

Database: SQL, data validation and backend verification.

Testing Methodologies: Functional, integration, regression and end-to-end testing.

Additional exposure to LangGraph, LangChain, MCP, Azure OpenAI and AI Agents can provide an advantage.


🎯 Expected Interview Rounds

Round 1 – Recruiter Screening: Experience, AI-testing background, notice period, remote-work suitability and compensation expectations.

Round 2 – QA/Automation Technical Round: Selenium/Playwright/Cypress, API testing, SQL, automation frameworks and software-testing methodologies.

Round 3 – AI Testing Round: This is likely to be the most important round. Expect scenario-based questions around hallucinations, prompt regression, context retention, intent routing, groundedness and AI response evaluation.

Round 4 – Practical/Design Discussion: You may be asked to design an AI testing strategy or framework for a chatbot or AI agent.

Round 5 – Managerial/Final Round: Ownership, communication, problem-solving and experience handling production-quality issues may be evaluated.


πŸ’° Salary Range

The vacancy does not mention a fixed salary.

For 5–9 years of experienced AI/QA automation professionals in India, a broad market-oriented expectation could be approximately β‚Ή12–30+ LPA, depending heavily on AI-testing depth, automation expertise, location, employer type and seniority.

This is a market estimate, not a confirmed salary range for this vacancy.


πŸ”₯ Preparation Tips

Don’t prepare like a traditional Selenium interview.

Take a hypothetical customer-support AI chatbot and create a complete testing strategy.

Test:

πŸ”Ή Incorrect intent classification
πŸ”Ή Context loss between messages
πŸ”Ή Prompt injection attempts
πŸ”Ή Hallucinated answers
πŸ”Ή Unsupported claims
πŸ”Ή Poorly grounded responses
πŸ”Ή Tool/API failures
πŸ”Ή Authentication failures
πŸ”Ή Fallback and escalation
πŸ”Ή Conversation loops
πŸ”Ή Model-version regression

Then design an automated evaluation approach.

Also understand the difference between traditional pass/fail testing and AI evaluation using metrics such as relevance, groundedness, correctness and consistency.


πŸ“„ Resume Tips

Your resume must clearly demonstrate that you have actually tested AI systems.

Avoid:

❌ β€œUsed ChatGPT for testing.”

Instead write:

βœ… β€œDesigned automated regression scenarios for LLM-powered conversational workflows, validating intent routing, context retention and response quality.”

Strong keywords to include naturally:

AI Quality Engineering | LLM Testing | Generative AI Testing | Conversational AI | AI Agents | Prompt Testing | Model Regression | AI Evaluation | Groundedness | Hallucination Testing | Playwright | Selenium | Cypress | Python | REST API | Postman | SQL | E2E Testing | LangChain | LangGraph | MCP


πŸ“© How to Apply

Interested candidates meeting the 5–9 years requirement and possessing genuine AI-testing experience can share their updated CV at:

πŸ“§ sonali.shraiya@programming.com

⚑ Immediate joiners only according to the vacancy.

Before applying, make sure your resume specifically demonstrates hands-on experience with AI/LLM/Chatbot testing. Candidates whose only AI exposure is using ChatGPT or Copilot for ordinary development/testing work may not match the requirement.


πŸš€ Final Takeaway

This opportunity is particularly relevant for experienced QA professionals who want to transition from traditional automation into AI Quality Engineering.

The key differentiator isn’t simply knowing ChatGPTβ€”it is understanding how AI systems fail and how those failures can be systematically detected, measured, automated and prevented.

If you can combine strong QA fundamentals with LLM evaluation, conversational testing, AI-agent validation and modern automation, this type of role can position you strongly for the rapidly growing AI testing market. πŸ€–πŸš€


Rohit BARAHATE

Rohit BARAHATE is a Quality Engineering Specialist with 4.6+ years of experience in the IT industry. With a network of over 123K+ LinkedIn connections and actively supports job seekers by sharing referral opportunities and guiding them toward successful careers.

Join WhatsApp

Join Now

Join LinkedIN

Join Now

Leave a Comment