The client is looking for a Senior Consultant / Manager to support enterprise AI governance across traditional machine learning, GenAI, and emerging agentic AI use cases. This is a business-facing role, but it requires strong technical depth in AI engineering, model testing, evaluation, and risk assessment.
The ideal candidate should be able to work with business, technology, risk, compliance, legal, and finance teams while also understanding how AI systems are designed, built, tested, monitored, and governed in production.
Key Responsibilities
Support AI intake, governance reviews, and portfolio tracking across supervised ML, GenAI, and agentic AI initiatives.
Review AI solution designs, data flows, model architecture, RAG/LLM workflows, testing evidence, monitoring approach, and control gaps.
Assess AI risks related to model performance, hallucination, bias, explainability, data privacy, security, compliance, and operational impact.
Partner with AI engineers, data scientists, architects, risk, compliance, and business stakeholders to move AI use cases through the governance process.
Create AI governance documentation, process guidance, executive updates, status reports, and presentation materials.
Support ROI tracking, dependency management, issue/risk escalation, and special projects such as AI application inventory reconciliation.
Required Skills
7–10+ years of experience in AI/ML, AI engineering, data science, model governance, technology risk, enterprise architecture, or technical program leadership.
Strong understanding of supervised machine learning, GenAI, LLMs, RAG, agentic AI, model testing, model evaluation, and production AI controls.
Ability to assess technical AI risks and translate them into clear business, governance, and compliance language.
Strong stakeholder management, executive communication, documentation, PowerPoint, Excel, and structured problem-solving skills.
Experience in financial services, banking, insurance, or another regulated industry is strongly preferred.
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