Vice President, AI Platform Engineering

About the Role

A leading enterprise undergoing a bold AI transformation is seeking a Vice President of AI

Platform Engineering to architect and scale its next-generation AI platform. Reporting directly to the Chief AI Officer, this executive will build the foundation that powers AI-native products and intelligent agentic systems across the organization.

This is a high-impact opportunity to shape the enterprise’s AI platform strategy from the ground up — enabling rapid experimentation, deployment, and governance of AI at scale. You’ll collaborate closely with product, data, infrastructure, and security leaders to convert cutting-edge AI innovation into measurable business outcomes.

Key Responsibilities

• AI Platform Strategy: Define and execute the enterprise AI platform vision, ensuring scalability, security, and cost efficiency for AI product and agent development.

• Platform Architecture: Design and operate robust AI/ML platforms including model lifecycle management, feature stores, vector databases, orchestration frameworks, observability, and governance tooling.

• Agentic Systems Enablement: Build foundational capabilities to support multi-agent systems, LLM deployments with RAG, orchestration frameworks, and agentic SDKs.

• MLOps and LLMOps Excellence: Establish CI/CD pipelines, model evaluation, and monitoring systems to ensure safe, fast, and reliable AI deployments.

• Security & Governance: Partner across functions to implement responsible AI practices, data privacy controls, auditability, and governance standards.

• Data & Integration: Collaborate with Data Engineering on lakehouse architecture, semantic layers, and real-time data flows that power AI applications.

• Cross-Functional Alignment: Lead through structured governance forums to ensure AI platform priorities align with enterprise strategy and shared business outcomes.

• Team Leadership: Build and lead a world-class AI platform engineering organization with a culture of technical excellence, accountability, and innovation.

• Vendor & Ecosystem Strategy: Evaluate and integrate best-in-class AI technologies and cloud solutions to accelerate transformation.

• Optimization: Drive performance, reliability, and cost optimization across AI workloads and infrastructure.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (advanced degree preferred).

• 12+ years of engineering leadership experience, including 5+ years in AI/ML platform engineering or large-scale distributed systems.

• Proven track record of building and scaling enterprise AI platforms or AI infrastructure at scale.

• Deep expertise in MLOps, LLMOps, modern ML frameworks (e.g., PyTorch, TensorFlow), vector databases, RAG, and AI agent orchestration.

• Strong understanding of AI security, governance, and operational performance metrics.

• Demonstrated success in productionizing AI-native applications and integrating agentic workflows into business operations.

• Exceptional communication, strategic influence, and cross-functional leadership skills.

Why Apply?

This is a rare opportunity to shape the foundation of an enterprise-wide AI transformation — with the autonomy, executive visibility, and resources to deliver real innovation at scale. If you’re passionate about building AI platforms that redefine how organizations operate, we’d love to connect.