Data for AI Testing Lead

Job Description:

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

Technical Requirements:

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

Strong 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

Additional Responsibilities:

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 CD

Preferred Skills:

Technology->AI-Generative AI->Generative AI - Basic,Technology->AI-Data science->PYTHON