AI Platform Engineering Director

Role Overview

This position provides strategic and technical leadership for the enterprise AI platform engineering function, setting the technology strategy and reference architecture for how AI is built, deployed, and scaled enterprise-wide. The role is accountable for building and operating shared AI engineering capabilities that enable teams to develop, deploy, monitor, evaluate, and scale AI solutions safely and efficiently.

You will define the architecture, standards, and roadmap for shared enterprise AI platform capabilities, balance AI operations, MLOps/LLMOps, and agentic frameworks, lead engineering practices for model and AI-system deployment, monitoring, testing, evaluation, versioning, reliability, and lifecycle management, and contribute to the enterprise AI technology maturity view.

You will lead teams responsible for MLOps, LLMOps, AI operations, platform engineering, GIS or other assigned platform capabilities, and related AI engineering functions, build reusable engineering frameworks and capabilities, and establish production support and operational run patterns.

• Demonstrated experience leading engineering teams that build production platforms, internal developer platforms, MLOps/LLMOps capabilities, AI operations, or scalable AI/ML systems
• Experience with AI system architecture, model deployment, agent deployment, monitoring, observability, evaluation, production support, and lifecycle management
• Demonstrated ability to balance operational reliability with emerging agentic workflow and LLM pipeline frameworks
• Experience creating reusable frameworks, standards, and platform capabilities that improve delivery across multiple teams
• Familiarity with GenAI, agentic workflows, LLM pipelines, model orchestration, retrieval-augmented generation patterns, model gateways, systems-of-record integration, and emerging AI platform patterns
• Demonstrated experience with production support models, including L1/L2 support expectations and engineering-side L3 support
• Experience with cost, capacity, resilience, usage monitoring, routing, fallback, caching, or Fin Ops practices for cloud or AI workloads
• Experience working across Information Security, Enterprise Architecture, Infrastructure, Cloud, Application Development, Digital Services, Data Engineering, Governance, Legal, Risk, Compliance, and business domains
• Experience managing or coordinating partners such as GCP, AWS, Data Dog, or related technology vendors
• Demonstrated people leadership, technical coaching, prioritization, and talent development skills

• Comprehensive medical, dental, vision and wellbeing benefits
• Competitive 401(k) contribution
• Pension plan
• Annual incentive
• 9 paid holidays
• Paid time off program (23 days accrued annually for full-time employees)
• Student loan repayment program
• Paid-family leave