Key Responsibilities

Core Engineering & Testing
Design and implement scalable, maintainable automation frameworks for API and backend systems.
Own end-to-end test strategy across functional, system, and integration layers.
Build robust API automation suites using Java (Rest Assured/Karate) and contemporary tooling.
Collaborate closely with developers, product managers, and DevOps teams in an agile environment to ensure high-quality releases.
Design and validate AI-generated test cases for APIs, including authentication flows, request chaining, and error handling.
Build and maintain QA agentic systems capable of:
Auto-generating test cases from requirements
Detecting coverage gaps across services
Suggesting missing edge cases and negative scenarios
Test AI-based applications (LLMs, copilots, intelligent services) for correctness, hallucination risks, and robustness across edge cases.
Define testing strategies for non-deterministic systems, including:
Prompt evaluation frameworks
Response validation heuristics
Dataset-driven testing

Quality Intelligence & Platform Thinking
Build tools that provide real-time visibility into test coverage, risk areas, and defect patterns.
Leverage AI/ML techniques for:
Defect clustering and root cause analysis




Test optimization and prioritization
Contribute to internal QA platforms such as API coverage mapping and intelligent test generation systems.

Mandatory Skills & Requirements
5–8 years of experience in API testing and automation.
Robust programming skills in Java (preferred) or Python/Golang.
Hands-on experience with API automation frameworks such as Rest Assured, Karate, or similar tools.
Robust understanding of REST APIs, microservices architecture, request/response validation, and authentication flows.
Experience in test planning, strategy, and execution across multiple system layers.
Ability to analyze logs, debug failures, and collaborate with stakeholders for issue resolution.
Practical exposure to AI tools for test generation, with the ability to refine and productionize outputs.
Minimum 1 year of hands-on experience in AI projects involving RAG Models, Multi-Agent Systems, or Generative AI is mandatory.
Candidates should currently be working with Product-based companies only.

Skills:- Java, Rest Assured, Karate, API, Large Language Models (LLM) tuning, Generative AI and Artificial Intelligence (AI)

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