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.