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 Apply tot his job