The Role
Tests conversational and agentic AI applications through functional, regression, integration, performance, security, and end-to-end testing. Validates LLM accuracy, RAG, prompts, agent reasoning, workflows, tool integrations, guardrails, safety, bias, and responsible AI behavior. Develops test strategies, reports defects in JIRA, produces quality metrics, and contributes to automated AI testing frameworks and evaluation pipelines while collaborating with product, engineering, data science, and prompt engineering teams.
Summary Generated by Built In
Quality Assurance (QA) Engineer – Conversational AI & Agentic AI
Job Overview
We are looking for a Quality Assurance (QA) Engineer with 3-7 years of experience in testing, QA, and reporting, specifically within the field of Conversational AI and Agentic AI systems. The ideal candidate will have a strong understanding of standard testing practices and be passionate about ensuring the highest quality standards in AI-driven applications. This role involves validating conversational experiences, AI-powered workflows, autonomous agent behaviors, integrations with external tools and APIs, and ensuring the reliability, safety, and performance of AI systems in production environments.
Key Responsibilities
- 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 to ensure quality standards are met 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 capabilities, including multi-agent collaboration, task decomposition, context management, memory retention, and tool utilization.
- Identify, document, and track defects using JIRA and provide detailed reports on testing results.
- Analyze requirements and design comprehensive 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 to validate compliance with organizational and regulatory standards.
- Generate test reports, dashboards, and quality metrics for stakeholders, ensuring clear and actionable insights.
- Contribute to the continuous improvement of AI testing processes, frameworks, methodologies, and automation capabilities.
Required Qualifications
- 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.
Desired Qualifications
- Experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar platforms.
- Experience with automated testing tools and scripting languages (Python, JavaScript, etc.).
- Exposure to NLP, NLU, LLM evaluation, prompt testing, and AI model validation.
- Knowledge of cloud AI platforms such as Google CCAI/Dialogflow, Azure AI, AWS Bedrock, Amazon Lex, or OpenAI-based solutions.
- Familiarity with version control systems (Git, GitHub, Azure DevOps).
- Experience developing AI test automation frameworks and evaluation pipelines.
- Understanding of Responsible AI principles, AI governance, model monitoring, and risk assessment.
Personal Attributes
- Attention to detail and a commitment to delivering high-quality work.
- Strong communication and stakeholder management skills, both written and verbal.
- Self-motivated with a passion for AI innovation, quality engineering, and continuous improvement.
- Ability to manage multiple priorities in a dynamic, fast-paced environment.
- Curiosity to explore emerging AI technologies and evaluate complex AI agent behaviors.
- Strong critical thinking skills with the ability to identify risks, edge cases, and quality gaps in AI systems.
Preferred Experience Areas
- Conversational AI Testing (Chatbots, Voicebots, Virtual Assistants)
- Generative AI & LLM Testing
- Agentic AI Testing
- RAG Validation
- Prompt Testing and Optimization
- AI Safety & Responsible AI Testing
- API and Integration Testing
- Test Automation
- Cloud-based AI Solutions
Quality Assurance (QA) Engineer – Conversational AI & Agentic AI
Job Overview
We are looking for a Quality Assurance (QA) Engineer with 3-7 years of experience in testing, QA, and reporting, specifically within the field of Conversational AI and Agentic AI systems. The ideal candidate will have a strong understanding of standard testing practices and be passionate about ensuring the highest quality standards in AI-driven applications. This role involves validating conversational experiences, AI-powered workflows, autonomous agent behaviors, integrations with external tools and APIs, and ensuring the reliability, safety, and performance of AI systems in production environments.
Key Responsibilities
- 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 to ensure quality standards are met 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 capabilities, including multi-agent collaboration, task decomposition, context management, memory retention, and tool utilization.
- Identify, document, and track defects using JIRA and provide detailed reports on testing results.
- Analyze requirements and design comprehensive 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 to validate compliance with organizational and regulatory standards.
- Generate test reports, dashboards, and quality metrics for stakeholders, ensuring clear and actionable insights.
- Contribute to the continuous improvement of AI testing processes, frameworks, methodologies, and automation capabilities.
Required Qualifications
- 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.
Desired Qualifications
- Experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar platforms.
- Experience with automated testing tools and scripting languages (Python, JavaScript, etc.).
- Exposure to NLP, NLU, LLM evaluation, prompt testing, and AI model validation.
- Knowledge of cloud AI platforms such as Google CCAI/Dialogflow, Azure AI, AWS Bedrock, Amazon Lex, or OpenAI-based solutions.
- Familiarity with version control systems (Git, GitHub, Azure DevOps).
- Experience developing AI test automation frameworks and evaluation pipelines.
- Understanding of Responsible AI principles, AI governance, model monitoring, and risk assessment.
Personal Attributes
- Attention to detail and a commitment to delivering high-quality work.
- Strong communication and stakeholder management skills, both written and verbal.
- Self-motivated with a passion for AI innovation, quality engineering, and continuous improvement.
- Ability to manage multiple priorities in a dynamic, fast-paced environment.
- Curiosity to explore emerging AI technologies and evaluate complex AI agent behaviors.
- Strong critical thinking skills with the ability to identify risks, edge cases, and quality gaps in AI systems.
Preferred Experience Areas
- Conversational AI Testing (Chatbots, Voicebots, Virtual Assistants)
- Generative AI & LLM Testing
- Agentic AI Testing
- RAG Validation
- Prompt Testing and Optimization
- AI Safety & Responsible AI Testing
- API and Integration Testing
- Test Automation
- Cloud-based AI Solutions
Bachelor's/Master's in Engineering 2-5 years
About Us EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
Skills Required
- 3-7 years of experience in software testing and quality assurance, including exposure to Conversational AI, Generative AI, Agentic AI, or similar 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 LLMs, RAG, prompt engineering concepts, and AI agent architectures
- Experience using 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 with 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 or Master's degree in Engineering
- Experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar platforms
- Experience with automated testing tools and scripting languages such as Python or JavaScript
- Exposure to NLP, NLU, LLM evaluation, prompt testing, and AI model validation
- Knowledge of cloud AI platforms such as Google CCAI, Dialogflow, Azure AI, AWS Bedrock, Amazon Lex, or OpenAI-based solutions
- Familiarity with Git, GitHub, or Azure DevOps
- Experience developing AI test automation frameworks and evaluation pipelines
- Understanding of Responsible AI, AI governance, model monitoring, and risk assessment
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
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The Company
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
