Job Overview
| Particulars | Details |
|---|---|
| Position | Quality Engineer – Test Automation & AI Assurance |
| Company | Kotsonit Solutions |
| Job Type | Remote |
| Experience | 4 - 5 years |
| Category / Department | IT |
| Application Mode |
🏢 About Kotsonit Solutions
Company Overview:
Established in 2005, Kotsonit Solutions is an HR and managed workforce solutions provider offering customized IT services to corporate clients in the IT industry. The company focuses on connecting organizations with skilled professionals and supporting workforce requirements through talent acquisition expertise, industry knowledge, and customized solutions.
Company Mission:
To empower businesses by connecting them with the right talent, supporting flexible workforce requirements, and helping employees find meaningful and rewarding work opportunities.
Company Vision:
To create a hub of workflow excellence and help organizations reach their highest potential through effective talent and workforce solutions.
Core Values / Principles:
- Client commitment and relationship building
- Understanding business and talent requirements
- Workforce flexibility
- Talent empowerment
- Industry expertise
- Technology-driven solutions
- Performance and results orientation
💡 Editor's Note / Preparation Tip
Resume Tips:
- Clearly mention 5+ years of experience in Test Automation or Quality Engineering.
- Highlight hands-on experience with Playwright, Cypress, Pytest, API testing, and contract testing.
- Include practical examples of LLM and AI agent evaluation.
- Showcase RAG testing experience, including grounding, citation validation, and hallucination detection.
- Mention AI security testing experience involving prompt injection, jailbreaks, and data leakage.
- Include examples of CI/CD integration, test data management, and production monitoring.
Interview Preparation:
- Prepare to explain your automation framework architecture and testing strategy.
- Revise API testing, contract testing, and service-level testing concepts.
- Understand how to evaluate RAG applications and detect hallucinations.
- Prepare practical examples of AI Red Teaming and adversarial testing.
- Be ready to discuss AI quality thresholds, canary releases, A/B testing, and model drift monitoring.
Professional Tips:
- Demonstrate the difference between traditional software testing and AI/LLM assurance.
- Explain how you measure AI response quality, reliability, and safety.
- Prepare examples of real-world defects or risks identified through automation and AI testing.
📝 Job Description
Position Details:
- Role: Quality Engineer – Test Automation & AI Assurance
- Work Mode: Remote
- Experience: 5+ years
- Domain: Test Automation, Quality Engineering, AI/LLM Assurance
Role Overview:
The selected candidate will build reliable test automation solutions and validate the quality, accuracy, safety, and reliability of AI/LLM-powered applications. The role combines traditional software quality engineering with specialized testing of AI agents, RAG systems, and GenAI applications.
Benefits / Compensation:
Not Provided.
Candidate Requirements:
- 5+ years of experience in Test Automation or Quality Engineering.
- Hands-on experience with UI automation tools such as Playwright, Cypress, or similar.
- Experience with Pytest or equivalent service-level testing frameworks.
- Strong API and contract testing knowledge.
- Experience with test data management and CI/CD.
- Practical experience evaluating LLMs and AI agents.
- Understanding of RAG testing, grounding, citations, and hallucination detection.
- Experience with AI Red Teaming and adversarial testing.
- Ability to validate AI response accuracy and quality.
- Experience testing prompt injection, jailbreaks, data leakage, and unsafe tool usage.
Preferred Skills:
- Strong combination of automation engineering and hands-on GenAI/LLM testing.
- Experience defining AI release quality thresholds.
- Experience with canary and A/B testing for AI or model changes.
- Production monitoring for model drift, guardrail violations, and user feedback.
- Practical use of AI tools to improve QA and testing productivity.
Working Days & Hours:
Not Provided.
How to Apply:
Interested candidates can share their updated CV at mamatha.p@kotsonit.com.
🎯 Key Responsibilities
- ✓ Build and maintain reliable test automation frameworks.
- ✓ Develop UI automation tests using Playwright, Cypress, or similar tools.
- ✓ Perform service-level testing using Pytest or equivalent frameworks.
- ✓ Execute API and contract testing.
- ✓ Manage test data and support CI/CD testing workflows.
- ✓ Evaluate LLM-powered applications and AI agents.
- ✓ Test RAG applications for grounding, citation quality, and hallucination detection.
- ✓ Validate AI response accuracy, consistency, and overall quality.
- ✓ Perform AI Red Teaming and adversarial testing.
- ✓ Test AI applications for prompt injection, jailbreaks, data leakage, and unsafe tool usage.
- ✓ Define quality thresholds and release criteria for AI-powered applications.
- ✓ Support canary and A/B testing for AI and model changes.
- ✓ Monitor production AI systems for model drift, guardrail violations, and user feedback.
- ✓ Use AI tools to improve QA workflows and testing productivity.
💡 Required Qualifications & Skills
🚀 Career Guidance & Interview Insights
To help you succeed, we've compiled original preparation guides, resume keywords, and growth analytics for this category of role.
Joining as a Quality Engineer – Test Automation & AI Assurance offers a fantastic opportunity to work at the forefront of technological innovation. You will be exposed to modern software development lifecycles, collaborate with cross-functional product teams, and design scalable architectures that directly impact end-users. The continuous learning curve in tech ensures that your programming, debugging, and system engineering skills remain highly marketable and sharp.
The career roadmap in technology is highly rewarding. Typical progression starts as a Junior Software Engineer, moving to Associate Developer and then Senior Software Engineer (3-6 years). From there, professionals choose between an individual contributor track—becoming a Tech Lead, Staff Engineer, and Principal Architect—or a management track, advancing to Engineering Manager, Director of Engineering, and Chief Technology Officer (CTO).
Expected Technical & Behavioral Questions:
- Q1: How do you optimize database query performance?
Answer Tip: Talk about indexing strategies, query execution plan analysis, avoiding N+1 queries, and implementing caching layers (like Redis). - Q2: Explain the differences between Microservices and Monolithic architecture.
Answer Tip: Highlight scaling advantages, loose coupling, independent deployments, network latency considerations, and data consistency challenges in microservices. - Q3: How do you handle merge conflicts in Git?
Answer Tip: Explain checking out the local branch, pulling the latest main branch, running git merge, opening the conflicted files to resolve blocks manually, and committing the resolved merge.
To pass automated ATS (Applicant Tracking System) screening and catch the recruiter's eye, tailor your resume with the following tips:
- Keywords to include: Software Engineering, SDLC, OOP, CI/CD Pipelines, SQL databases, Agile, Unit Testing, Code Review, Cloud Architectures (AWS/Azure).
- Format: Use a clean, single-column resume format. Avoid graphics, text boxes, or tables which can scramble ATS parser outputs.
- Quantify Results: Instead of writing 'wrote code', write 'Developed a caching system that reduced server response times by 35%.'
Estimated compensation for this role type in India is ₹6,00,000 - ₹12,00,000 per annum (Mid level). The actual salary package offered depends on factors such as company size, work mode (remote or on-site), individual technical proficiency, and negotiations during final HR rounds.
Highly recommended certifications include: AWS Certified Solutions Architect, Microsoft Certified: Azure Fundamentals, Certified Kubernetes Administrator (CKA), Oracle Certified Professional Java SE, or tech-stack specific achievements (e.g. Meta Front-End Developer certification).
Frequently Asked Questions
Q1. What is the job title?
Quality Engineer – Test Automation & AI Assurance.
Q2. What is the work mode?
Remote.
Q3. What is the minimum experience required?
5+ years.
Q4. Which UI automation tools are required?
Playwright, Cypress, or similar UI automation tools.
Q5. Is Pytest experience required?
Yes. Pytest or an equivalent service-level testing framework is required.
Q6. Is API testing required?
Yes. Strong API and contract testing experience is mandatory.
Q7. Is AI/LLM testing mandatory?
Yes. Hands-on LLM and AI agent evaluation experience is mandatory.
Q8. What AI testing areas are covered?
RAG testing, grounding, citation validation, hallucination detection, response quality, and AI security testing.
Q9. Which AI security testing skills are required?
Prompt injection, jailbreak, data leakage, unsafe tool usage, and adversarial testing.
Q10. How can candidates apply?
Candidates can share their CV at mamatha.p@kotsonit.com.
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