Job Summary

We are seeking a Software Engineer 4 (AI Test Engineer) to support the development, testing, and delivery of AI-enabled Identity and Access Management (IAM) solutions. This role is responsible for designing automated testing frameworks, validating AI/ML applications, ensuring enterprise software quality, and supporting modern DevOps and CI/CD practices. The ideal candidate will have strong experience in software engineering, quality engineering, Java, React, JavaScript, AI/ML testing, enterprise IAM platforms, and automated testing within highly regulated environments.

Key Responsibilities
• Design, develop, test, debug, and maintain enterprise software solutions supporting Identity and Access Management (IAM) initiatives.
• Lead the design and implementation of automated testing strategies for enterprise web applications and AI-enabled platforms.
• Develop and maintain automated testing frameworks using Java, JavaScript, React, and modern automation technologies.
• Design and execute comprehensive test plans covering functional, integration, system, performance, stress, security, API, and data quality testing.
• Define and monitor AI quality metrics, including model accuracy, fairness, explainability, robustness, performance, and security.
• Validate AI/ML models, Large Language Models (LLMs), prompt-response workflows, contextual understanding, and AI-generated outputs.
• Perform bias testing, data validation, model evaluation, and AI system reliability testing.
• Conduct security testing and vulnerability assessments for AI-enabled and enterprise applications.
• Build reusable automation components and integrate automated testing into CI/CD pipelines using Jenkins, GitHub Actions, or similar tools.
• Support testing and validation of IAM platforms, including Access Automation, Identity Governance, Privileged Access Management (PAM), Attribute-Based Access Control (ABAC), self-service access management, and enterprise access request solutions.
• Test REST APIs using Postman or similar API testing tools.
• Collaborate with engineers, architects, product managers, business analysts, and stakeholders to ensure complete testing coverage.
• Participate in Agile ceremonies, including sprint planning, backlog refinement, sprint reviews, and retrospectives.
• Document, prioritize, track, and resolve software defects while communicating quality metrics, project risks, and testing progress.
• Mentor engineering and quality assurance team members while promoting software quality best practices and continuous improvement initiatives.

Required Qualifications
• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent professional experience.
• Minimum of 5 years of software engineering experience.
• Minimum of 5 years of software testing experience supporting enterprise web applications.
• Strong software development experience using Java, JavaScript, and React.
• Experience supporting enterprise IAM applications, access management solutions, or enterprise security platforms.
• Experience building and maintaining automated testing frameworks.
• Experience integrating automated testing into CI/CD pipelines using Jenkins, GitHub Actions, or similar technologies.
• Hands-on experience with functional, integration, system, performance, stress, security, and API testing.
• Experience testing REST APIs using Postman or similar tools.
• Experience with Git and modern version control practices.
• Experience implementing quality assurance processes and testing strategies for enterprise software applications.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent verbal, written, communication, and stakeholder management skills.
• Experience working in Agile software development environments.

Preferred Qualifications
• Experience validating AI/ML systems, Large Language Models (LLMs), prompt engineering workflows, and AI-enabled applications.
• Knowledge of Machine Learning, Neural Networks, Natural Language Processing (NLP), Generative AI, and AI model evaluation techniques.
• Experience with data validation, data quality assurance, and large-scale dataset testing.
• Experience performing application security testing, vulnerability assessments, secure software validation, and secure software development lifecycle practices.
• Experience with cloud-native applications deployed on Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
• Experience supporting DevSecOps initiatives and enterprise automation programs.
• Experience with Selenium, SpecFlow, Vulcan, or similar automated testing frameworks.
• Experience using Atlassian tools, including Jira and Confluence.
• Experience working within highly regulated enterprise environments.
• Ability to collaborate effectively within geographically distributed and matrixed organizations.