Job description

*Please apply only if you are suitable for the job description below.*

Required Skills & Experience
- 5+ years of experience in Data Quality Engineering, Analytics Testing, or Data driven transformation programs.
- 5+ years leading AI Data Assurance, AI/GenAI, Analytics, or AI Quality Engineering initiatives
- Strong knowledge of AI/ML, GenAI, LLMs, various RAG Architectures, Prompt Engineering, Vector Databases, DataOps/MLOps, and AI Governance.
- Robust expertise in ETL Testing, Analytics & BI Testing, Reporting Validation, AI Data Readiness Assurance, AI Data Harness Assurance, AI Data Outcome Assurance and Continuous AI Assurance
- Hands-on Experience with Cloud Data & AI Platforms such as Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, or similar.
- Strong leadership, stakeholder management, communication, and mentoring skills.





Technical & Professional Requirements
- Agile Delivery, Quality Governance
- AI Data Assurance, AI/ML, GenAI, LLMs & RAG Architectures
- Data Quality, Data Governance & Responsible AI
- ETL, Data Warehouse, Analytics, BI & Data Integration Testing
- SQL, Snowflake, Databricks, Informatica & Azure Data Factory (ADF)
- Prompt Engineering & Retrieval Assurance
- Python, PySpark & Test Automation
- Playwright, API Testing
- Vector Databases, AI Data Pipelines, DataOps & MLOps
- Azure, AWS & GCP Data & AI Platforms
- Jira, Zephyr, Azure DevOps & CI/CDRole & responsibilities

Preferred candidate profile

Perks and benefits

📌 DATA For AI (India)
🏢 Infosys
📍 India