VP of AI Technology & Operations

VP, AI Technology & Operations

The VP, AI Technology & Operations serves as the senior technical leader within Our Client's Enterprise AI organization, reporting directly to the SVP, Enterprise AI. This role is the operational and engineering backbone of the Enterprise AI team delivering measurable EBITDA impact across the enterprise.

This leader will directly manage the AI Technology & Innovation, AI Product Operations, AI Enablement, and AI Compliance & Risk functions. While AI/ML engineers are embedded within product teams and report through those teams day-to-day, the VP, AI Technology & Operations serves as their technical mentor, architectural authority, and engineering career anchor across the full organization.

The ideal candidate is a technically deep practitioner — experienced in machine learning, agentic AI systems, cloud infrastructure, and enterprise automation — who can also communicate complex technical concepts clearly to senior business stakeholders. This person thrives at the intersection of engineering excellence and operational delivery, and is comfortable moving between production system architecture and executive-level strategic conversation.

Responsibilities Technology Leadership & Architecture

• Serve as the senior-most technical expert in the AI & Automation organization, setting engineering standards and architectural direction across all AI products and platforms.
• Lead the evaluation, selection, and integration of AI/ML frameworks, LLM platforms, agentic systems, and cloud infrastructure (AWS) that power Our Client's AI portfolio.
• Function as technical mentor and engineering career sponsor for all AI/ML Engineers across the organization, regardless of product team assignment.
• Define and maintain best practices for model development, prompt engineering, agentic workflow design, RAG architectures, and production AI system deployment.
• Maintain hands-on technical fluency across the stack, including Python, cloud-native AI services, API integrations, and enterprise data pipelines.

AI Product Operations & Delivery

• Oversee the Senior Director of AI Product Operations to ensure delivery cadences, Scrum ceremonies, and product team support structures function effectively across the organization.
• Drive operational rigor across the product teams, including intake governance, sprint delivery, and benefit realization tracking tied to financial targets.
• Partner with Product Managers and Product Owners to translate business requirements into technical architectures and delivery plans.
• Ensure AI products are deployed reliably, monitored effectively, and continuously improved against defined KPIs (containment rates, cost savings, CSAT, handle time).

AI Enablement & Workforce Development

• Oversee the Director of AI Enablement to ensure enterprise-wide AI literacy programs, Enterprise AI Productivity Suite adoption, and citizen developer initiatives are well-resourced and impactful.
• Champion a "through people, not to people" AI transformation narrative, ensuring AI tools multiply human capability rather than simply reduce headcount.
• Drive adoption of AI tools and automation across business functions through structured training, use-case identification, and enablement programming.

AI Compliance, Risk & Governance

• Lead the build-out of the AI Compliance & Risk function, including responsible AI frameworks, vendor risk assessments, model governance policies, and data privacy controls.
• Ensure all AI deployments meet regulatory, ethical, and internal risk standards, including compliance with governance requirements.
• Partner with Legal, IT Security, and enterprise risk teams to establish a consistent AI governance posture across the organization.

Technical Qualifications

• Deep hands-on experience with large language models (LLMs), generative AI, agentic AI frameworks, and RAG-based architectures in production environments.
• Proficiency in Python and AI/ML development; experience with cloud AI services (AWS SageMaker, Bedrock, or equivalent).
• Experience designing and deploying conversational AI systems, voice AI, and contact center AI platforms.
• Familiarity with enterprise automation platforms and integration patterns across CRM, billing, and telephony systems.
• Strong understanding of MLOps practices: model monitoring, versioning, deployment pipelines, and production reliability.
• Experience with enterprise data platforms and data governance, including working knowledge of data engineering, API design, and cloud infrastructure.

Leadership & Business Qualifications

• 7 to 10+ years of progressive technical leadership experience, with demonstrated success leading engineering or AI/ML teams in a complex enterprise environment.
• Proven ability to communicate complex technical topics clearly to non-technical executive audiences, including board-level stakeholders.
• Experience managing multi-disciplinary technical teams, including engineers, analysts, and product operations staff.
• Track record of delivering AI or automation programs with measurable financial impact (cost savings, revenue generation, or efficiency gains).
• Strong cross-functional collaboration skills; ability to navigate IT, operations, finance, legal, and business stakeholders simultaneously.
• Experience working in PE-backed or high-accountability enterprise environments preferred.
• Contact center or operational AI experience strongly preferred.
• Bachelor's degree in Computer Science, Engineering, or related field required; advanced degree a plus.