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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in software testing and quality assurance for Conversational AI and Agentic AI applications, with a strong focus on functional, regression, and performance testing. Proficient in utilizing testing tools and methodologies to ensure compliance with AI evaluation metrics and responsible AI principles.
Highest-signal resume keywords
Conversational AI TestingJIRA Defect TrackingLarge Language Models (LLMs)API Testing ToolsAutomated Testing Frameworks
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software TestingQuality AssuranceTest Case DevelopmentRegression TestingPerformance TestingFunctional TestingData AnalysisPrompt EngineeringAI Model ValidationSecurity Testing
Soft Skills
Analytical SkillsProblem-Solving SkillsCollaborationAdaptabilityCommunication
Tools & Technologies
JIRAExcelPostmanSwaggerGitGitHubAzure DevOpsGoogle CCAI/DialogflowAWS BedrockOpenAI Solutions
Certifications & Qualifications
Bachelor's in EngineeringMaster's in Engineering
Industry Keywords
Conversational AIGenerative AIAgentic AINLPNLUAI GovernanceModel MonitoringRisk AssessmentAI Evaluation MetricsResponsible AI
Tech Stack
Tools & technologiesAWSAzureCloudJavaScriptPythonSDLC
About the role
Key responsibilities & impact- Develop and execute test cases, scripts, and procedures for Conversational AI and Agentic AI applications
- Collaborate with product managers, developers, data scientists, prompt engineers, and other stakeholders throughout the development lifecycle
- Perform functional, regression, integration, performance, and end-to-end testing across conversational AI platforms and agent-based AI systems
- Validate AI agent decision-making, task execution, multi-step workflows, reasoning paths, and interactions with external tools, APIs, and knowledge sources
- Test LLM-powered applications for accuracy, relevance, consistency, hallucinations, guardrail compliance, and response quality
- Evaluate agent orchestration, including multi-agent collaboration, task decomposition, context management, memory retention, and tool utilization
- Identify, document, and track defects using JIRA and provide detailed testing reports
- Analyze requirements and design test strategies covering conversational flows, autonomous agent behaviors, integrations, and edge-case scenarios
- Conduct prompt, response, and workflow validation to ensure optimal performance and user experience
- Perform security, privacy, bias, and responsible AI testing for organizational and regulatory compliance
- Generate test reports, dashboards, and quality metrics for stakeholders
- Contribute to continuous improvement of AI testing processes, frameworks, methodologies, and automation capabilities
Requirements
What you’ll need- 3–7 years of experience in software testing and quality assurance, with exposure to Conversational AI, Generative AI, Agentic AI, or similar AI technologies
- Strong knowledge of QA methodologies, SDLC, STLC, defect management, and validation techniques
- Experience testing conversational AI platforms, chatbots, voicebots, virtual assistants, or AI-driven applications
- Understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering concepts, and AI agent architectures
- Experience with JIRA for defect tracking and project management
- Strong proficiency in Excel for data analysis, reporting, and test metrics
- Familiarity with API testing tools such as Postman, Swagger, or equivalent
- Experience in functional, integration, performance, security, and user acceptance testing
- Understanding of AI evaluation metrics, model behavior analysis, and conversational testing frameworks
- Ability to work effectively in cross-functional teams and adapt to fast-paced environments
- Strong analytical, troubleshooting, and problem-solving skills
- Bachelor's/Master's in Engineering
- Desired: experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar platforms
- Desired: experience with automated testing tools and scripting languages such as Python and JavaScript
- Desired: exposure to NLP, NLU, LLM evaluation, prompt testing, and AI model validation
- Desired: knowledge of cloud AI platforms such as Google CCAI/Dialogflow, Azure AI, AWS Bedrock, Amazon Lex, or OpenAI-based solutions
- Desired: familiarity with version control systems such as Git, GitHub, or Azure DevOps
- Desired: experience developing AI test automation frameworks and evaluation pipelines
- Desired: understanding of Responsible AI principles, AI governance, model monitoring, and risk assessment
Benefits
Comp & perks- No benefits, perks, or compensation extras are specified in the posting