Exp-3-7 years

Role Summary

We are looking for a highly skilled QA Engineer specializing in AI-enabled systems, intelligent automation, and enterprise AI validation. The role involves testing AI-native applications, AI agents, orchestration workflows, cloud-integrated systems, and AI-assisted SDLC solutions across multiple delivery tracks including CGS, SDS, ETL, modernization, APIs, cloud-native systems, and legacy platforms.

The ideal candidate should possess strong expertise in AI testing strategies, automation frameworks, cloud-native testing, API validation, AI harness creation, and scalable deployment validation.

Key Responsibilities

• Design and execute testing strategies for AI-native applications, AI agents, and enterprise AI workflows.


• Build AI testing harnesses and automated validation frameworks for LLM-based systems.


• Validate RAG pipelines, prompt flows, agent orchestration, APIs, and enterprise integrations.


• Perform functional, integration, regression, security, and performance testing for AI-enabled systems.


• Validate AI agent behavior, hallucination risks, guardrails, prompt responses, and orchestration reliability.


• Work with AI-assisted testing ecosystems including Amazon Q Developer, AWS Kiro/Cairo, GitHub Copilot, Claude, OpenAI, and related tools.


• Support testing and validation of scalable deployments across Docker, Kubernetes, and cloud-native environments.


• Collaborate with developers, architects, DevOps teams, and business stakeholders to ensure production readiness.


• Support continuous testing within Azure DevOps/GitHub CI/CD pipelines.


• Drive observability, logging validation, monitoring validation, and runtime issue analysis for AI workloads.

Required Technical Skills

AI & Automation Ecosystem

• Hands-on exposure to:




• AWS Bedrock


• Amazon Q Developer


• AWS Kiro/Cairo


• Claude/OpenAI ecosystems


• GitHub Copilot




• Understanding of:




• AI agents


• RAG architectures


• Prompt engineering


• Vector databases


• LangChain/LangGraph


• AI orchestration workflows

QA & Automation Expertise

• Strong experience in:




• API testing


• Automation testing


• Functional testing


• Regression testing


• Integration testing


• Data validation




• Hands-on with:




• Postman


• SoapUI


• SQL


• Python


• AI testing harnesses


• Test automation frameworks

Cloud & Platform Knowledge

• Understanding of:




• AWS cloud ecosystem


• Docker containerization


• Kubernetes orchestration


• CI/CD pipelines


• Azure DevOps


• GitHub Actions


• Cloud-native deployments

Security & Governance

• Understanding of:




• IAM/security concepts


• AI guardrails


• Prompt security


• Enterprise governance


• Runtime monitoring and observability

Mandatory Practical Experience

• Must demonstrate hands-on testing experience for AI-enabled enterprise applications and AI agents.


• Experience validating AI workflows, orchestration pipelines, and enterprise integrations.


• Must have worked on automation-heavy delivery environments and AI-assisted SDLC ecosystems.


• Experience validating scalable deployments across containerized/cloud-native environments.


• Strong troubleshooting, analytical, and stakeholder communication capabilities.


• High learning agility with ability to rapidly adapt to evolving AI ecosystems and enterprise technology stacks.