QA Analyst with AI

Tekskills; Pune District; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Tekskills is seeking a QA Associate Engineer (AI Testing) to join our Pune/Bangalore/Hyderabad projects. The role is on-site or hybrid depending on the project, targeting 4–7 years of QA experience with an emphasis on AI and LLM testing.

You will design adversarial and robustness tests, validate data pipelines, and integrate LLM test suites into CI/CD workflows. Strong communication and defect documentation are essential for collaboration with engineering teams.

Qualifications

• 4+ years in software QA with AI focus.
• Experience with AI testing and LLM behavior.
• Hands-on with data pipelines and test data management.

Responsibilities

• Test AI solutions with emphasis on LLM behavior, bias, and hallucinations.
• Design robust test cases via prompt engineering and adversarial testing.
• Validate data pipelines, training and retrieval data, and synthetic data coverage.
• Integrate LLM test suites into CI/CD pipelines (Azure DevOps, GitHub Actions).
• Document defects and support triage with engineering teams.

Skills

LLM Behavior

Prompt Engineering

Photo Validation

CI/CD Integration

Test Case Generation

RAG Evaluation

Guardrails Testing

Data Pipeline Testing

Synthetic Data

Defect Documentation

Tools

Azure DevOps

GitHub Actions

Job description

We are currently hiring for a QA Testing Engineer AI Focused role, and your profile seems to match our requirements.

Please find the job details below:

Position: QA Associate Engineer (AI Testing)

Experience: 4 to 7 Years

Location: Pune / Hyderabad / Bangalore (On-site/Hybrid – as per project)

Job Description – QA Associate Engineer

Minimum Experience:

• At least 4 years of experience in software quality assurance, with a focus on AI solutions.

Must Have Hands-On Experience In:

• Deep understanding of LLM behaviour, including hallucinations, bias, and edge-case handling.
• Prompt engineering to design adversarial and robustness test cases.
• Conducting photo validation and recognition tests to ensure accuracy in AI-driven quality audits.
• Integrating LLM-focused test suites into CI/CD pipelines (Azure DevOps, GitHub Actions).
• LLM test case generation, RAG evaluation, and use of guardrails for secure, explainable testing.
• Strong background in data pipeline testing, ensuring input/output integrity of training and retrieval systems.
• Managing test data, generating synthetic data, and auditing data coverage.
• Documenting defects clearly and supporting triage with engineering teams.