Head of Responsible AI - Director

C iti Wealth Management is seeking a senior technology leader to establish and lead enterprise capabilities for AI evaluation, observability, guardrails, and governance supporting Generative AI, AI agents, and machine learning systems across advisor and client platforms.

This role will define and implement enterprise frameworks that ensure AI and agent-based systems are reliable, safe, explainable, and compliant with financial services regulations.

The ideal candidate will bring deep hands-on experience building and deploying AI and agent-based solutions at enterprise scale, while providing strategic leadership to develop platforms and governance models that enable responsible and scalable AI adoption across Wealth Management.

Key Responsibilities

AI Evaluation Framework (Evals)

Lead the design and implementation of enterprise evaluation frameworks to measure performance, safety, and reliability of AI models, Generative AI systems, and AI agents.

Responsibilities include: • Define evaluation methodologies for LLMs, AI agents, and ML models • Develop benchmark datasets and automated evaluation pipelines • Implement testing frameworks for accuracy, hallucination detection, bias, and reasoning quality • Establish AI performance metrics and quality KPIs • Enable continuous evaluation across AI development and production pipelines

AI Observability & Monitoring

Establish enterprise observability capabilities to monitor the behavior and performance of AI systems.

Responsibilities include: • Build end-to-end observability frameworks for AI and agent workflows • Monitor model performance, response quality, latency, and drift • Enable traceability across prompts, models, tools, and agent decision flows • Implement real-time dashboards, monitoring, and alerts • Provide operational insights for AI reliability and performance

Guardrails & Responsible AI

Develop enterprise guardrails and governance frameworks to ensure safe and compliant AI usage.

Responsibilities include: • Define AI safety and governance standards • Implement prompt injection protection and output validation • Enforce PII protection and regulatory compliance controls • Establish human-in-the-loop workflows • Ensure compliance with Responsible AI and enterprise AI policies

AI Agent Governance

Define governance models for autonomous and semi-autonomous AI agents deployed across wealth management systems.

Responsibilities include: • Establish agent lifecycle management frameworks • Implement agent versioning, monitoring, and auditability • Define policies for agent decision boundaries and tool usage • Ensure agents operate within enterprise risk and compliance frameworks

Enterprise Collaboration

Partner with technology and business teams across the organization.

Responsibilities include: • Collaborate with AI engineering, data science, product, risk, enterprise and compliance teams • Align AI capabilities with wealth management strategic priorities • Support AI-driven platforms for advisor insights, client servicing assistants, research intelligence, and marketing personalization

Hands-on Enterprise AI Implementation

This role requires deep hands-on experience designing and deploying AI and agent systems in large-scale enterprise environments, preferably within financial services.

Candidates should demonstrate: • Hands-on experience deploying AI models, Generative AI applications, and AI agents in production • Building evaluation pipelines and testing frameworks • Implementing AI observability and monitoring platforms • Designing guardrails and safety controls for AI systems • Delivering enterprise AI capabilities across multiple business use cases

AI Tools & Technology Ecosystem

Hands-on experience working with modern AI frameworks, agent orchestration platforms, and foundation models.

Agent Frameworks & Orchestration

Experience with platforms such as: Lang Chain Lang graph Lang Smith ADK LlamaIndex

AI Models

Experience evaluating and deploying models such as: GPT, Gemini, Claude, Mistral, Llama

Required Experience • 15+ years of overall technology experience in AI/ML, data platforms, or enterprise technology leadership. • Minimum 5+ years of hands-on AI implementation experience designing and deploying AI solutions at scale within large enterprise environments, preferably in financial services. • Demonstrated experience implementing Generative AI, AI agent systems, and machine learning solutions in production. • Experience building AI evaluation frameworks, observability platforms, and AI guardrails. • Strong understanding of AI governance, model risk management, and regulatory compliance. • Proven ability to lead enterprise AI initiatives and drive adoption across multiple teams.

Leadership Expectations • Define enterprise standards for AI governance, safety, and reliability • Lead development of AI observability and evaluation platforms • Enable scalable adoption of AI and agent-based systems • Mentor and lead cross-functional AI platform teams • Drive innovation while maintaining strong risk and compliance controls

Job Family Group: Technology

Job Family: Applications Development

Time Type: Full time

Most Relevant Skills Please see the requirements listed above.

Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

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