Gen AI Validator, Officer

Citi

. Conduct independent reviews and substantive challenge of AI and machine learning systems throughout their full lifecycle .

Posted 9/23/2026full-timeMumbai • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in assessing and validating AI and machine learning systems within financial services, focusing on risk management, regulatory compliance, and stakeholder communication. Proficient in applying advanced analytical techniques and methodologies to enhance AI risk frameworks and practices.

Highest-signal resume keywords

Master's Degree In Mathematics, Statistics, Computer Science, Engineering, Data Science, AI, Or Machine Learning4+ Years Of Analytics Experience In Financial Services2+ Years Focused On Generative AI Or Machine LearningHands-On Technical Knowledge Of AI And Machine Learning TechniquesExperience In Model Validation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Risk AssessmentMachine Learning ImplementationModel ValidationRisk Policy ComplianceData AnalysisStatistical AnalysisGenerative AI TechniquesAgentic AI TechniquesMethodology DevelopmentRegulatory Examination Preparation

Soft Skills

Stakeholder EngagementClear CommunicationCritical AssessmentTime ManagementCollaboration

Industry Keywords

Financial ServicesRisk ManagementRegulatory ComplianceGovernanceAI ValidationOperational RiskMarket RiskCredit RiskAnalyticsAI Frameworks

About the role

Key responsibilities & impact

Conduct independent reviews and substantive challenge of AI and machine learning systems throughout their full lifecycle
Identify and clearly communicate AI and machine learning risks to stakeholders
Assess AI and machine learning implementations against risk policies, testing standards, and procedural requirements
Engage with AI developers, sponsors, governance teams, internal audit, and regulators
Provide evidence-based challenge and guidance on AI-related risk matters
Validate and enhance methodologies used to measure and monitor market, credit, and operational risks
Prepare and contribute to responses for internal and external regulatory examinations
Contribute to the design and continuous improvement of AI risk frameworks, programmes, and practices
Collaborate on strategic initiatives within the model risk management organisation
Advance standards and best practices across the AI validation function

Requirements

What you’ll need

Master's degree or above in mathematics, statistics, computer science, engineering, data science, AI, machine learning, or a related quantitative field
4 or more years of analytics experience in financial services or a related industry
At least 2 years focused on Generative AI, Agentic AI, or machine learning
Hands-on technical knowledge of common AI and machine learning techniques
Ability to critically assess AI and machine learning applications and limitations in a financial context
Experience working in financial services
Understanding of the risk, regulatory, and governance landscape relevant to AI systems
Ability to communicate complex technical findings clearly and concisely to technical and non-technical audiences
Ability to manage multiple concurrent workstreams, meet deadlines, and maintain quality
Strong stakeholder engagement skills
Prior experience in model validation is beneficial

Benefits

Comp & perks

Hybrid working arrangement with 3 days in the office and 2 days working remotely
Exposure to the full spectrum of AI sub-fields, including Generative AI, Agentic AI, computer vision, and anomaly detection
Opportunity to contribute to strategic, cross-functional initiatives influencing AI governance standards across global markets and business lines
Continuous learning and professional development
Access to cutting-edge AI and risk management practices
Performance-driven environment where analytical contributions are visible, valued, and connected to business outcomes
Competitive financial wellbeing and benefits
Long-term career pathways across risk, AI, and financial services