QA Engineer AI-Gen AI TESTING (India)

Job Description Quality Engineering Lead

Role Overview

We are seeking a Quality Engineering Lead to drive the delivery of AI Data Assurance initiatives

by ensuring trusted, high-quality, and AI-ready data foundations. This role is responsible for

defining quality strategies, establishing AI Data assurance frameworks, driving automation, and

ensuring trusted, high-quality, AI-ready data foundations that enable reliable, responsible, and

business-aligned AI outcomes.

The ideal candidate will have strong experience in Data Testing, AI Data Assurance, Analytics

Testing, AI/ML Data Validation, and Quality Engineering, along with a solid understanding of

AI/GenAI ecosystems, LLMs, RAG architectures, DataOps/MLOps, and Responsible AI practices.

Key Responsibilities

Project & Delivery Leadership

Lead end-to-end delivery of AI Data Assurance programs.

Drive delivery governance, quality metrics, executive reporting, and Agile/Hybrid

delivery excellence.

Quality Engineering, AI Assurance & Governance

Define quality strategies, testing frameworks, and assurance processes for AI/ML,

GenAI, AI data assurance, analytics, and BI platforms.

Govern end-to-end validation, release readiness, and quality gates.

Lead testing and validation of data platforms, pipelines, analytics solutions, BI platforms

and AI-ready datasets.

Implement AI Data Harness Assurance across data pipelines, RAG systems, vector stores,

and AI workflows.

Drive AI Data Outcome Assurance by evaluating AI output quality, reliability,

explainability, and business alignment.

Support Responsible AI, AI Governance, and Model Assurance initiatives.

Automation, Client Orientation & Team Leadership

Build automation frameworks for AI Data Assurance, BI assurance and continuous

quality monitoring.

Embed quality controls and assurance gates within DataOps, MLOps, and CI/CD

pipelines.

Lead and mentor AI Data Assurance teams and drive capability development, quality

reviews, and continuous improvement.

Collaborate with business, product, data engineering, architecture, AI/ML, and platform

teams to deliver AI transformation initiatives.

Drive automation, AI assisted testing, capability development, and continuous

improvement initiatives.

Build AI data assurance accelerators and participate in client demos

Contribute to client pursuits, solutioning, proposals, estimations, and AI assurance

offerings.

Build partnerships, thought leadership assets, innovation frameworks, webinars,

workshops, and knowledge-sharing initiatives.

Required Skills & Experience

5+ years of experience in Data Quality Engineering, Analytics Testing, or Data driven

transformation programs.

3+ years leading AI Data Assurance, AI/GenAI, Analytics, or AI Quality Engineering

initiatives

Solid knowledge of AI/ML, GenAI, LLMs, various RAG Architectures, Prompt

Engineering, Vector Databases, DataOps/MLOps, and AI Governance.

Strong 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

Compensation: 1,800,000.00 - 2,000,000.00 per year

Work Location: Remote .
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