AI Delivery VP

Job description

Position Overview

The Vice President – AI Delivery leads the global delivery organization for Teleperformance’s AI products and solutions under the TP.ai FAB ecosystem.

This executive role is accountable for the successful implementation, scalability, and continuous performance of FAB-enabled solutions — ensuring each deployment delivers measurable business value and operational impact.

The VP ...oversees cross-functional squads covering AI Solution Architecture, Full-Stack and Data Engineering, Application Delivery, and Solutioning, driving excellence across design, build, and rollout phases.

Partnering with Product, Engineering, and Operations leaders, this role ensures that FAB’s delivery engine operates at enterprise scale — agile, secure, compliant, and results-driven.

Key Responsibilities

• Delivery Leadership & Governance

· Lead the global AI Delivery organization, encompassing Architecture, Development, Data, and Application Delivery teams.

· Establish and maintain consistent delivery frameworks, standards, and KPIs across all AI and digital solution projects.

· Ensure delivery squads follow FAB’s Process → Product → Pilot → Rollout → Success lifecycle and comply with governance guidelines.

· Oversee project portfolio execution, risk management, and delivery forecasting.

• AI Solutions & Technical Excellence

· Provide executive oversight for the design, build, and implementation of AI-powered products and client-specific solutions.

· Partner with the AI Solutions Architects to define end-to-end architectures that are secure, scalable, and interoperable.

· Drive the technical roadmap and architecture reusability for FAB’s Foundation, Enablement, and Blueprint layers.

· Ensure all deployments meet performance, compliance, and Responsible AI standards.

• Operational Performance & Execution

· Monitor run-rate, delivery velocity, and quality assurance across multiple concurrent global projects.

· Implement continuous improvement mechanisms (automation, observability, delivery analytics).

· Align capacity planning, resource optimization, and delivery productivity to business growth targets.

· Ensure high reliability and on-time delivery through proactive governance, issue management, and escalation processes.

• Cross-Functional Collaboration

· Work closely with Product Management, Engineering, and Operations to ensure seamless transition from design to delivery to support.

· Partner with Finance and PMO for delivery budgets, forecasting, and prioritization.

· Engage directly with global clients and business sponsors to represent delivery strategy, progress, and success outcomes.

• People Leadership & Organizational Development

· Lead a global team of AI Solution Architects, Full-Stack Engineers, Data Engineers, QA, and Product Delivery Managers.

· Build and mentor a high-performance organization centered on accountability, transparency, and innovation.

· Foster a culture of excellence, continuous learning, and Responsible AI awareness across all teams.

· Support talent acquisition and development in alignment with FAB Academy and AI skill frameworks.

• Strategic Transformation & Innovation

· Evolve FAB Delivery capabilities toward next-generation, AI-first, and cloud-native delivery models.

· Champion innovation in solutioning, automation, and AI enablement.

· Lead strategic delivery partnerships with hyperscalers, vendors, and internal technology hubs.

· Translate emerging technology trends into actionable delivery strategies and frameworks.

Required Qualifications

Educational Background

· Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or Information Systems.

· MBA or Executive Program in Digital Transformation or Technology Leadership preferred.

Experience

· 15+ years of experience in technology and AI solution delivery, including 5+ years in a global leadership role.

· Proven track record managing large-scale software, data, and AI delivery organizations.

· Experience leading cross-functional teams across architecture, engineering, and client delivery.

· Strong background in AI architecture, ML engineering, and productized delivery models.

· Familiarity with cloud ecosystems (Azure, AWS, GCP) and AI frameworks (LangChain, TensorFlow, PyTorch).

· Hands-on understanding of Responsible AI, data governance, and platform observability.

Technical Skills

· Expertise in enterprise architecture, MLOps, API ecosystems, and microservices.

· Strong command of DevSecOps, CI/CD, and modern cloud-native delivery frameworks.

· Understanding of LLM orchestration, GenAI pipelines, and AI model lifecycle.

· Experience in

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