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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Papigen • India
Role & seniority
Stack/tools
API test automation (functional, integration, performance, security)
CI/CD integration and orchestration
AI/ML quality validation (model evaluation, drift, fairness, monitoring)
Scalable automation frameworks; governance and documentation practices
Collaboration across QA Leads, Tech Leads, and Engineering teams
Top 3 responsibilities
Own end-to-end testing strategy for API and AI/ML capabilities across multiple squads; ensure alignment with QA/engineering governance.
Design, build, and maintain scalable automated test suites for APIs (functional, integration, regression, performance, security) fully integrated into CI/CD with quality gates.
Define and execute AI/ML testing strategies (model validation, output quality, bias/fairness checks, drift detection, edge-case testing) and establish continuous model monitoring and validation post-deployment.
Must-have skills
Bachelor’s degree in CS or equivalent; 5+ years API test automation (functional/integration/performance/security) with strong CI/CD experience
Proficiency with modern test automation frameworks/tools for API testing, performance testing, and CI/CD orchestration
Solid understanding of AI/ML quality concepts (model evaluation, fairness, drift, monitoring); hands-on preferred
Strong cross-team collaboration, communication, and ability to influence testing strategy
Role Overview
We are seeking an experienced AI Quality Engineer to own and drive end-to-end quality strategy for API and AI/ML platforms. This role focuses on building scalable automation frameworks, CI/CD-integrated validation pipelines, and robust AI testing standards to ensure accuracy, fairness, performance, and production reliability across services.
Key Responsibilities
Own the end-to-end testing strategy for API and AI/ML capabilities across multiple squads, working closely with QA Leads, Tech Leads, and Engineering teams. Design, build, and maintain scalable automated test suites for APIs, covering functional, integration, regression, performance, and security testing, fully integrated into CI/CD pipelines with defined quality gates. Establish and manage baseline evaluation datasets, golden tests, and acceptance thresholds for pre-deployment and post-deployment validation of APIs and AI models. Define and execute AI/ML testing strategies, including model validation, output quality assessment, bias and fairness checks, drift detection, edge-case testing, and continuous model monitoring. Ensure CI/CT pipeline reliability through proactive monitoring, alerting, rapid triage, root cause analysis, environment/data management, and performance optimization. Expand and standardize validation frameworks and test coverage across API and AI services, ensuring consistency across environments and compliance with engineering and governance standards. Drive shift-left testing by collaborating during solution design, sprint execution, and code reviews. Report on test health, risks, and quality metrics, contributing to governance forums and providing visibility into release readiness and quality trends.
Required Skills & Experience
Bachelor’s degree in Computer Science or equivalent practical experience. 5+ years of hands-on experience in API test automation, including functional, integration, performance, and security testing, with strong CI/CD integration. Proficiency with modern test automation frameworks and tools for API testing, performance testing, and CI/CD orchestration. Strong understanding of AI/ML quality validation concepts, including model evaluation, fairness, drift, and monitoring (hands-on experience preferred). Excellent cross-team collaboration and communication skills, with the ability to influence testing strategy and support multiple squads. Strong documentation, debugging, and problem-solving skills, with a proven record of improving test reliability and engineering quality maturity.
Nice to Have
Experience testing LLMs, ML inference APIs, or data-driven platforms Exposure to cloud-native CI/CD pipelines and distributed systems Familiarity with governance, compliance, or enterprise QA standards
Skills: api,ml,ai/ml,ci/cd,llm,automation,api test automation,testing