SVP, Chief AI Officer

Office of AI Leadership

• Define and execute enterprise AI strategy across internal productivity tools, customer offerings, and managed services
• Operate the AI platform layer, including model management, tooling, data pipelines, guardrails, and evaluation frameworks
• Drive organization-wide AI adoption through fluency programs, training, playbooks, and industry-specific solution accelerators
• Establish comprehensive AI governance covering risk management, compliance, security, safety, and model lifecycle management
• Own AI cost modeling and unit economics in partnership with Finance and Operations teams
• Manage GPU and CPU capacity strategy to optimize performance and cost

AI Strategy & Business Impact

• Own the AI platform roadmap, model portfolio, and evaluation and monitoring approaches
• Drive AI solution patterns for priority industries and embed AI capabilities into every product and service offering
• Measure and report AI value creation, including revenue impact, margin improvement, productivity gains, quality enhancements, and risk reduction
• Lead co-innovation initiatives with key technology partners and AI vendors
• Coordinate AI go-to-market strategy with Product and Sales organizations

AI Governance & Responsible AI

• Set comprehensive policies for responsible AI including ethical use, bias mitigation, and fairness
• Establish data usage policies, privacy protections, and regulatory compliance frameworks
• Define AI safety standards and incident response protocols
• Create transparency and explainability requirements for AI systems
• Monitor and enforce adherence to AI governance policies across the organization

CTO Collaboration & Platform Integration

• Ensure AI platform standards align with overall technology architecture established by the CTO
• Obtain joint approval with CTO for AI architectures that impact core platform decisions or risk posture
• Participate in quarterly technology and AI strategy reviews with integrated roadmaps
• Co-lead monthly architecture and model governance councils
• Coordinate on platform reliability, security, and cost optimization initiatives

Key Performance Indicators

• AI-attributed revenue and pipeline contribution
• AI-driven productivity improvements and cost savings
• AI adoption metrics across internal teams and customer base
• Model quality, performance, and safety scores
• AI platform reliability and uptime
• Cost per AI inference or transaction
• Compliance with AI governance policies and regulations
• Partner ecosystem engagement and co-innovation outcomes
• Customer satisfaction with AI-powered solutions

Technical Expertise

• Deep expertise in AI/ML technologies, large language models, and generative AI
• Strong understanding of AI platform architecture, MLOps, and model lifecycle management
• Knowledge of AI safety, bias mitigation, explainability, and responsible AI practices
• Familiarity with cloud infrastructure, data engineering, and modern software development practices
• Understanding of AI regulatory landscape and compliance requirements

Leadership Capabilities

• Strategic thinker who can translate AI capabilities into business value and competitive advantage
• Exceptional communication skills with the ability to educate and influence at all organizational levels
• Proven ability to drive adoption and change management across large organizations
• Experience building and leading multidisciplinary AI teams, including researchers, engineers, and data scientists
• Track record of partner management and ecosystem development
• Strong business acumen withan understanding of go-to-market and monetization strategies

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field required
• Advanced degree (Master's or PhD) in AI, Machine Learning, Computer Science, or related field strongly preferred
• MBA or equivalent business education a plus
• 12+ years of progressive technology and AI leadership experience with at least 5 years in senior executive roles
• Proven track record building and scaling AI/ML platforms, products, or practices in enterprise environments
• Experience driving AI strategy that delivers measurable business outcomes and revenue impact
• History of establishing AI governance frameworks and responsible AI programs
• Experience managing large-scale AI infrastructure, model operations, and GPU/compute resources

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