About ETS : ETS is a global education and talent solutions organization enabling lifelong learners worldwide to be future-ready. For more than 75 years, we've been advancing the science of measurement to build benchmarks for fair and valid skill assessment across cultures and borders. Our worldwide impact extends through our renowned assessments including TOEFL®, TOEIC®, GRE® and Praxis® tests, serving millions of learners in more than 200 countries and territories. Through strategic acquisitions, we've expanded our global capabilities: PSI strengthens our workforce assessment solutions, while Edusoft, Kira Talent, Pipplet, Vericant, and Wheebox enhance our educational technology and assessment platforms across critical markets worldwide. Through ETS Research Institute and ETS Solutions, we're partnering with educational institutions, governments, and organizations globally to promote skill proficiency, empower upward mobility, and unlock opportunities for everyone, everywhere. With offices and partners across Asia, Europe, the Middle East, Africa, and the Americas, we deliver nearly 50 million tests annually. Join us in our journey of measuring progress to power human progress worldwide. - Position Summary The Staff Agentic AI Engineer - Quality Automation Platform & Modernization is responsible for designing, developing, and maintaining agentic AI workflows that transform enterprise quality artifacts into reviewable, traceable, executable quality automation assets. This role is a senior hands-on engineering position within the AI Quality Automation Transformation CoE and focuses on building the agentic workflow layer, reusable prompt patterns, tool integrations, automation generation logic, and modernization pathways for existing automation assets.



The role develops workflows that ingest data and artifacts from systems such as Jira, GitLab, Confluence, Figma, and Zephyr; process that context through specialized AI agents; and generate automation scripts and executions. This role also supports modernization of the existing automation estate. Recent AI-first workflows must be designed with awareness of current conventional automation frameworks including functional and performance testing, pipeline execution, and regression-maintenance dependencies. The role helps classify existing automation assets for reuse, refactoring, regeneration, migration, or retirement while protecting current regression capability.

Primary Responsibilities

- Design, build, and maintain AI agentic workflows for quality automation, including ingestion, context refinement, scenario generation, script generation, review, and repository integration.
- Develop and maintain AI agents for quality engineering use cases, including Jira issue analysis, Zephyr test case ingestion, Confluence/Figma context retrieval, GitLab script generation, code refactoring, and automation output validation.
- Build reusable prompt libraries, workflow templates, agent instructions, and validation patterns for positive, negative, edge, regression, PPV, integration, performance and E2E scenarios.
- Generate or support generation of automation scripts and quality assets using Playwright/JavaScript and other approved automation technologies.




- Develop transition patterns that allow existing automation frameworks and solutions, and manual regression assets to be analyzed, reused, refactored, regenerated, or retired.
- Partner with the Principal AI Quality Architect to implement architecture standards, governance requirements, and reusable design patterns.
- Integrate agentic workflows with enterprise tools and repositories, including Jira, Zephyr, GitLab, Confluence, Figma, and future approved sources.
- Support comparison of AI-generated automation outputs against existing automation baselines, including effort, traceability, stability, maintenance, and execution readiness.
- Document workflow designs, prompt patterns, integration assumptions, known limitations, operating instructions, and reusable implementation guidance.

LI-AD1 Experience and Skills :

- Strong software engineering skills with Python and/or JavaScript/TypeScript.
- Hands-on experience of Performance Testing across multiple technologies including Cloud Native, Serverless, Client Server, SalesForce stacks.
- Hands-on experience with automation frameworks such as Playwright, Selenium, or comparable test automation technologies.
- Working knowledge of REST APIs, OpenAPI specifications, Git-based workflows, repository automation, and CI/CD integration patterns.
- Practical experience with LLMs, prompt engineering, RAG/context retrieval patterns, agentic workflows, or AI-assisted software engineering.
- Experience integrating with Jira, Zephyr, GitLab, Confluence, Figma, or similar enterprise engineering systems.
- Ability to analyze existing test cases, requirements, defects, scripts, logs, and automation outputs to identify reusable context and modernization paths.
- Strong understanding

📌 Staff Ai Agentic Automation Engineer (Delhi)
🏢 Educational Testing Service (ETS)
📍 Delhi