Head of AI

Head of AI
Location: New York, NY
Full Time Opportunity- 3 days in the office

Role Overview
The Head of AI is a cross-functional executive leader responsible for shaping the AI vision, building the AI roadmap, and delivering high-impact capabilities across the platform. This role combines hands-on technical expertise with executive-level strategy, ensuring that AI investments drive measurable business value while meeting the highest standards of security, compliance, and responsible AI. This role will report to the Chief Technology Officer.
You will partner closely with Engineering, Product, Security, Operations, and Go-To-Market teams to deliver production-ready AI capabilities that support internal workflows, enrich our product suite, and strengthen competitive position.
Responsibilities

Strategy & Leadership

· Define and own company-wide AI strategy and long-term roadmap.
· Establish and lead the AI Center of Excellence, including governance, best practices, and enterprise enablement.
· Identify and prioritize high-impact AI opportunities across product, platform, and operations.
· Communicate AI strategy, progress, and insights to executives, clients, partners, and investors.

Technical Direction

· Architect and guide development of AI/ML systems and tools (LLMs, RAG, ML pipelines, agent frameworks, etc.).
· Evaluate, select, and integrate enterprise-grade AI solutions that align with Ninth Wave's security and regulatory standards.
· Build the foundation for scalable AI features, including model evaluation, monitoring, observability, and lifecycle management.
· Lead rapid prototyping and experimentation to validate and iterate on new AI-driven capabilities.

Compliance & Responsible AI

· Implement and enforce responsible AI policies (bias detection, privacy, transparency, auditability).
· Partner with Security and Compliance to ensure adherence to financial and regulatory frameworks (FFIEC, OCC, GLBA).
· Oversee development of clean, reliable, and AI-ready datasets within Ninth Wave's architecture.

Internal Enablement & Adoption

· Drive adoption of AI tools across teams to enhance productivity (engineering acceleration, customer support, sales enablement, risk analytics, and more).
· Develop and deliver internal training programs on AI capabilities, emerging technologies, and responsible use.
· Collaborate with Product to design AI-enabled features that solve real client problems.

Team Building

· Build and lead a world-class AI organization, including ML engineers, data scientists, and applied AI researchers.
· Foster a culture of innovation, secure-by-design thinking, and continuous learning.

Requirements
· 10+ years of experience in data science, machine learning, or AI engineering roles, including 3+ years in a leadership or executive capacity.
· Proven experience building and deploying AI/ML solutions in production environments.
· Deep understanding of modern AI/ML methodologies, including LLMs, multimodal models, vector databases, and distributed systems.
· Experience in regulated industries (fintech, banking, enterprise SaaS, etc.).
· Strong understanding of data privacy, security architecture, and responsible AI frameworks.
· Ability to translate complex AI concepts into clear business value for internal and external audiences.
· Exceptional communication, storytelling, and cross-functional leadership skills.

Experience with API-driven platforms, data connectivity products, or financial technology ecosystems.
· Hands-on familiarity with RAG architectures, agentic workflows, and enterprise AI infrastructure.
· Experience building corporate AI training programs or organizational AI enablement initiatives.
· Prior experience engaging directly with clients, regulators, or enterprise partners on AI topics.
· 10+ years of experience in AI/ML, with a proven track record of delivering enterprise-scale AI solutions in complex, highly regulated environments
· Deep expertise in AI technologies, machine learning, generative AI, data architecture, cloud platforms (AWS, Azure, Google Cloud Platform), and MLOps.
· A strong understanding of banking operations, open banking principles, risk management, and relevant regulatory landscapes.
· Exceptional communication, stakeholder management, and strategic thinking skills, with the ability to influence and educate technical and non-technical audiences.
· An advanced degree (Master's or PhD) in Computer Science, Data Science, AI, or a related field is typically preferred .