REGULATORY COMPLIANCE-CSV - GxP AI-Val Testing -Senior

EY; Hyderabad; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

EY is seeking a senior Regulatory Compliance GxP AI Validation/Testing expert to lead AI/ML validation across model lifecycles in regulated environments. You will drive risk-based testing, governance, and quality controls, collaborating with Product, Data Science, and Quality teams to ensure inspection-ready deliverables.

The role emphasizes Responsible AI, quality-by-design, and governance-by-design practices to enable safe, explainable AI in life sciences contexts.

Qualifications

• Bachelor's or master's degree in Life Sciences, Engineering, or related field.
• 5+ years of experience in AI/ML, GenAI, software testing, validation, or quality engineering roles.
• Experience creating user stories, test scripts, validation plans, or AI solution prototypes.
• Exposure to cloud ecosystems such as Azure, AWS, or GCP.
• Consulting or client-facing experience preferred.
• Excellent communication, documentation, and stakeholder management skills.

Responsibilities

• Lead the validation strategy for AI/ML and GenAI-enabled business solutions, ensuring compliance with GxP, CSV, CSA, risk management, and regulatory expectations.
• Author and maintain Validation Plans, Validation Strategies, Traceability Frameworks, Acceptance Criteria, and Validation Summary Reports for AI-integrated platforms and use cases.
• Define risk-based testing approaches for AI-enabled user workflows, focusing on functional suitability, business process integrity, intended use verification, and compliance requirements.
• Oversee front-end validation activities for AI-powered applications, ensuring user interactions, outputs, workflows, and decision-support functionalities perform as intended across business scenarios.
• Establish validation deliverables throughout the AI solution lifecycle, including requirement review, test planning, change assessment, release readiness reviews, and post-deployment monitoring support.
• Provide compliance oversight for AI solution delivery, ensuring validation evidence, documentation, and audit trails are complete, traceable, inspection-ready, and aligned with organizational quality standards.
• Collaborate with Product Owners, Business Stakeholders, Data Scientists, Engineers, and Quality teams to translate business requirements into testable validation and compliance objectives.
• Leverage observability and monitoring frameworks to assess AI system behaviour trends, identify deviations impacting validated state, and support ongoing compliance assessments.
• Coordinate defect triage, impact assessment, root cause discussions, and remediation activities while ensuring appropriate documentation and closure in accordance with quality processes.
• Manage release governance and stakeholder communications by facilitating validation reviews, compliance sign-offs, deployment readiness assessments, status reporting, and executive-level updates throughout the implementation lifecycle.

Skills

AI/ML experience

GenAI testing

CSV/CSA knowledge

Risk-based validation

Client-facing

Communication

Agile/Hybrid delivery

Validation planning

Regulatory compliance

Education

Bachelor's or master's degree in Life Sciences, Engineering, or related field

Tools

Azure

AWS

GCP

Langfuse

Arize

WhyLabs

MLflow

Azure AI Foundry Monitoring

Job description

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

EY- GDS Consulting Enterprise Risk (ER) Regulatory Compliance Senior GxP AI Validation/Testing

As part of our EY-ER- Regulatory Compliance team, you will help the clients by understanding their business needs and delivering solutions in accordance with the EY guidelines methodologies. As a Regulatory Compliance senior actively establish, maintain and strengthen internal and external relationships. In line with our commitment to quality, you’ll consistently drive projects to completion with high quality deliverables, achieve operational efficiency, proactively identify and raise risks with the client as well as EY senior management team and lead internal initiatives.

The opportunity

We are seeking a highly experienced and detail-oriented senior with strong expertise in validating AI/ML models, Generative AI (GenAI) systems, and multiagent workflows within GxP-regulated and quality-critical environments. The ideal candidate will ensure the reliability, fairness, robustness, and regulatory compliance of AI solutions while supporting cross-functional teams in designing, testing, and maintaining production-ready, inspection-ready AI systems.

This role is responsible for leading AI validation and testing activities across the full model lifecycle, including model development, training, testing, deployment, and post-deployment monitoring, in alignment with GxP principles, risk-based validation, and data integrity expectations. The consultant will play a key role in embedding Responsible AI, quality-by-design, and governance-by-design practices, enabling the safe, trustworthy, and explainable use of AI and agent-based solutions in regulated life sciences and pharmaceutical contexts.

Your key responsibilities

• Lead the validation strategy for AI/ML and GenAI-enabled business solutions, ensuring compliance with GxP, CSV, CSA, risk management, and applicable regulatory expectations.
• Author and maintain Validation Plans, Validation Strategies, Traceability Frameworks, Acceptance Criteria, and Validation Summary Reports for AI-integrated platforms and use cases.
• Define risk-based testing approaches for AI-enabled user workflows, focusing on functional suitability, business process integrity, intended use verification, and compliance requirements.
• Oversee front-end validation activities for AI-powered applications, ensuring user interactions, outputs, workflows, and decision-support functionalities perform as intended across business scenarios.
• Establish validation deliverables throughout the AI solution lifecycle, including requirement review, test planning, change assessment, release readiness reviews, and post-deployment monitoring support.
• Provide compliance oversight for AI solution delivery, ensuring validation evidence, documentation, and audit trails are complete, traceable, inspection-ready, and aligned with organizational quality standards.
• Collaborate with Product Owners, Business Stakeholders, Data Scientists, Engineers, and Quality teams to translate business requirements into testable validation and compliance objectives.
• Leverage observability and monitoring frameworks to assess AI system behaviour trends, identify deviations impacting validated state, and support ongoing compliance assessments.
• Coordinate defect triage, impact assessment, root cause discussions, and remediation activities while ensuring appropriate documentation and closure in accordance with quality processes.
• Manage release governance and stakeholder communications by facilitating validation reviews, compliance sign-offs, deployment readiness assessments, status reporting, and executive-level updates throughout the implementation lifecycle.

Qualifications

• Bachelor's or master's degree in Life Sciences, Engineering, or related field.
• 5+ years of experience in AI/ML, GenAI, software testing, validation, or quality engineering roles.
• Experience creating user stories, test scripts, validation plans, or AI solution prototypes.
• Exposure to cloud ecosystems such as Azure, AWS, or GCP.
• Consulting or client-facing experience preferred.
• Excellent communication, documentation, and stakeholder management skills.

Must-Have Skills And Attributes

• Strong understanding of Computer System Validation (CSV), Computer Software Assurance (CSA), GAMP 5, and risk-based validation approaches within regulated environments.
• Hands-on experience authoring Validation Plans, Validation Strategies, Test Plans, Traceability Matrices, Validation Summary Reports, and release readiness documentation.
• Proven experience leading validation activities for AI/ML-enabled, analytics, or digital transformation initiatives.
• Expertise in defining risk-based testing strategies, user acceptance criteria, and compliance-focused test approaches for AI-integrated business processes.
• Sound understanding of AI/ML system lifecycles, including data ingestion, model deployment, retraining considerations, and operational controls.
• Experience overseeing release management, defect management, deviation handling, and change control activities within validated environments.
• Knowledge of AI governance, validation documentation, audit preparedness, and regulatory expectations for AI-enabled systems.
• Ability to assess and maintain the validated state of AI solutions through monitoring, periodic review, and lifecycle management activities.
• Strong stakeholder management and communication skills, with experience collaborating across business, quality, product, engineering, and data science teams.
• Experience working within Agile/Hybrid delivery models while ensuring adherence to quality and compliance requirements.
• Experience in client-facing roles, managing expectations and delivering solutions
• Strong communication and presentation skills
• Experience in IT project management and validation planning
• Ability to troubleshoot application issues and recommend solutions
• Familiarity with change control, deviation handling, and CAPA processes
• Proven ability to mentor junior staff and lead validation teams
• Experience in training and cross-skilling resources
• Strong teamwork and collaboration mindset

Good-to-Have Skills And Attributes

• Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and multi-agent architectures.
• Familiarity with AI observability and monitoring frameworks, including model monitoring, drift detection, traceability, explainability, and operational risk tracking.
• Exposure to AI validation regulations and emerging industry guidance related to GxP AI systems and Responsible AI practices.
• Experience validating cloud-hosted AI platforms and solutions deployed on Azure AI, AWS AI/ML, or Google Vertex AI environments.
• Working knowledge of AI quality metrics, model performance indicators, and evaluation methodologies for supervised and unsupervised learning systems.
• Familiarity with observability and monitoring tools such as Langfuse, Arize, WhyLabs, MLflow, Azure AI Foundry Monitoring, or equivalent platforms.