Director of Artificial Intelligence, AI Strategy

Role Overview

At Kroll, our purpose is to bring clarity to complexity. As Director of Artificial Intelligence, you will shape and accelerate Kroll’s enterprise AI journey building the foundation for scalable, responsible, and business-aligned AI capabilities. You will partner across Kroll’s business lines to translate emerging AI technologies into measurable business and client outcomes. This role will be a critical participant in defining and operationalizing Kroll’s AI strategy and establishing technical standards and driving innovation that enhances insight and efficiency.

Key Responsibilities

Strategic Technical Leadership

• Collaborate on defining and executing Kroll’s AI Technology vision, strategy, and roadmap to deliver measurable business and client value, in coordination with internal stakeholders across the business
• Advise on AI trends, emerging technologies, and market dynamics partnering with AI business champion
• Continuously evaluate new AI tools, models, and vendors for strategic fit, scalability, and ROI potential in partnership with business champions and AI leader.
• Act as the champion responsible for ethical AI and delivery the reflects high integrity.

Architecture and Governance

• Define architectural principles and operating standards for scalable, secure, and ethical AI deployment.
• Lead the evaluation, design, and implementation of optimal cloud and on-premise architectures to support Kroll’s expanding portfolio of AI-driven internal and client solutions.
• Implement model lifecycle management practices from experimentation to monitoring and auditability.
• Collaborate with Infosec, Legal, Risk, Compliance, and Privacy to establish enterprise-wide AI governance for transparency, accountability, and regulatory compliance.
• Define and review model lifecycle management practices from experimentation to monitoring and auditability.

Technology and Engineering

• Provide recommendations and insights on AI/ML technologies, data architecture, and cloud ecosystems.
• Guide teams in developing, deploying, and operationalizing AI models at scale, including generative AI and LLM applications.
• Ensure alignment between research, engineering, and infrastructure teams to enable sustainable AI delivery.
• Translate business to technical requirements for R&D efforts focused on applied AI use cases, model evaluation, and emerging capabilities.
• Develop, implement, and manage an AI sandbox for experimentation and evaluation of new vendor and model capabilities.

Program and Delivery Management

• Partner with the AI strategy office to prioritize, execute, and scale AI initiatives across business units.
• Translate strategic goals into actionable programs spanning generative AI, automation, and advanced analytics
• Develop delivery frameworks to accelerate experimentation, and productionization of AI solutions aligned to Kroll priorities.
• Establish KPIs and reporting structures to measure adoption, value creation, and risk mitigation.

People and Capability Development

• Build and lead a multidisciplinary AI team encompassing data science, engineering, architecture, and change management
• Collaborate with relevant internal champions (i.e.Learning, Communications) to launch firmwide AI fluency programs and internal communities of practice to strengthen adoption and innovation.
• Partner with HR and business leaders to embed AI literacy across all levels of the organization through best-in-class learning and enablement initiatives.
• Foster a culture of innovation, collaboration and continuous learning aligned with Kroll’s value excellence, ambition, courage, integrity and inclusion.

External and Client Engagement

• Represent Kroll as a thought leader in AI ethics, governance, and innovation.
• Partner with AI leadership and business champions to co-create AI-powered solutions that strengthen insight, speed, and decision-making.
• Cultivate strategic alliances with hyperscalers, AI labs, and ecosystem partners to accelerate innovation.

Qualifications And Experience

• 12+ years of progressive leadership experience in data, analytics, or AI within a complex, global organization (preferably in professional or financial services).
• Demonstrated success in developing and operationalizing enterprise implementation of AI tooling and models.
• Deep understanding of modern AI/ML technologies, generative AI, and data architecture across cloud environments.
• Proven ability to translate AI R&D into production-grade, value-creating capabilities.
• Track record of program management with multi-disciplinary teams.
• Strong understanding of AI ethics, regulatory considerations, and responsible AI practices.
• Exceptional communication and stakeholder management skills, with the ability to bridge business and technical domains.
• Advanced degree in Computer Science, Engineering, Data Science, or equivalent experience preferred.

Skills Required

• Experience with LLMs (ChatGPT, Claude, CoPilot, Gemini, Llama, etc.)
• Fine-tuning, prompt engineering, and retrieval-augmented generation (RAG)
• Large-scale model training
• Neural network design (CNNs, RNNs, Transformers)
• Text classification, embeddings, sentiment analysis
• Strong foundation in Python, plus secondary languages (Java/Scala, C++, Go, Rust, etc.)
• API development (FastAPI, Flask)
• Version control (Git/GitHub)
• Unit testing, code optimization, and scalability

Key Attributes

• Purpose-Driven AI Builder: actively use and experiment with AI tools, translating emerging capabilities into practical solutions that serve clients responsibly and with integrity
• Strategic, Execution-Oriented Operator: ability to balance long-term vision with disciplined execution, prioritize what matters, and deliver measurable impact in fast-moving, ambiguous environments.
• Curious Systems Thinker: desire to go beyond the news cycle to deeply understand the AI landscape, connecting business needs to technical capabilities and identifying where AI creates real advantage.
• Collaborative Enterprise Leader: demonstrated ability to build strong, trust-based relationships across functions, levels, and geographies, leveraging diverse perspectives to drive innovation and inclusive outcomes.
• Client-Centric & Governance-Minded: ability to balance innovation with accountability — embedding security, privacy, and governance into AI solutions to deliver high-integrity results for clients.