Regulatory Compliance Manager - AI Model Consultant (GxP)

RC-REGULATORY COMPLIANCE-GxP AI Model Consultant-Manager At EY, youll 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 were 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 Manager GxP AI/Model Consultant 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 Manager actively establish, maintain and strengthen internal and external relationships. In line with our commitment to quality, youll 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 detailoriented AI Model Consultant with strong expertise in working alongside AI/ML models, Generative AI (GenAI) systems, and multiagent workflows within GxPregulated and qualitycritical environments. The ideal candidate will work on defining flows, integrate APIs and ensure the reliability, fairness, robustness, and regulatory adherence of AI solutions while working alongside crossfunctional teams in designing, testing, and maintaining productionready, inspectionready AI systems. This role is responsible for leading AI model consultation and development activities across the full model lifecycle, including model integration, training, testing, deployment, and postdeployment monitoring, in alignment with GxP principles, riskbased validation, and data integrity expectations. The consultant will play a key role in developing Model based use cases, leveraging qualitybydesign, and governancebydesign practices, enabling the safe, trustworthy, and explainable use of AI and agentbased solutions in regulated life sciences and pharmaceutical contexts. Your key responsibilities Lead AI and Agentic AI engagements from strategy through implementation and value realization. Design and oversee development of AI solutions leveraging LLMs, AI Agents, Multi-Agent Systems, RAG, Knowledge Graphs, and AI Orchestration frameworks. Drive client workshops to identify AI use cases, define target operating models, and develop AI roadmaps. Manage cross-functional teams including AI Engineers, Data Scientists, Architects, and Business Consultants. Establish AI governance, observability, risk management, model monitoring, and responsible AI practices. Support business development activities including proposals, solutioning, thought leadership, and client presentations. Perform AI/ML model integration, evaluation and validation across development, training, testing, and deployment phases. Evaluate model performance using precision, recall, accuracy, F1score, and confusion matrices. Gather and analyze business requirements and translate them into functional and technical solution designs. Configure, customize, and develop applications, workflows, data models, integrations, and reports based on business needs. Assess model behavior across datasets, edge cases, and failure scenarios to identify bias, drift, and instability. Demonstrate strong understanding of supervised and unsupervised learning models, including classification, regression, clustering, and anomaly detection. Conduct handson evaluation of GenAI and LLMbased systems, including prompt behavior, response quality, and consistency. Design and execute testing strategies for AI agents and multiagent workflows, covering orchestration logic, tool invocation, and output validation. Hands-on experience with APIs, scripting/programming, and system development lifecycle (SDLC). Use LangChain, LangGraph, and Langfuse for agent workflows, observability, traceability, and evaluation logging. Collaborate with data scientists and engineers to identify model improvement opportunities and risk mitigations. Qualifications: Bachelors or masters degree in Life Sciences, Engineering, or related field. 8+ 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 clientfacing experience preferred. Excellent communication, documentation, and stakeholder management skills. Must-Have Skills And Attributes Strong understanding of ML models, LLMs, GenAI workflows, agentic systems, and evaluation techniques. Strong foundation in machine learning concepts and model evaluation techniques. Handson experience with: Precision, Recall, Confusion Matrix .