Director, AI Infrastructure Operations

Huron•Chicago, IL

4d•$247,000 - $344,500•Remote

About The Position

The Director, AI Infrastructure Operations will lead the AI Operations team and run the day-to-day operations of Huron's governed AI capability within Corporate IT. This role combines operational leadership and people management with practical platform understanding: managing the team, the intake and prioritization process, the decision forums, and the delivery of the AI Operations roadmap. The role is designed to help teams move faster through appropriate governance by operating approved pathways, clear decision rights, reusable patterns, evidence standards, and measurable adoption goals. The person in this role should be comfortable using approved AI tools to develop artifacts, evaluate options, review technical approaches, and continuously improve the operating model. The capability is centered on AI infrastructure and platform operations rather than application development, though the team supports and contributes to solution delivery where needed. This role sits within AI Infrastructure Operations in Corporate IT, part of the CIO organization, with the CIO several levels above this role in the reporting line. It manages the AI Infrastructure Operations team, including the AI Infrastructure Architect and AI Infrastructure Engineer roles. The executive sponsor for the capability is the CIO.

Requirements

10+ years of experience in enterprise infrastructure, platform leadership, cloud operations, AI enablement, digital transformation, or enterprise architecture, including 3+ years directly managing technical teams or leading cross-functional platform work.
Demonstrated people management experience: hiring, developing, coaching, and performance management of technical staff.
Strong understanding of enterprise AI operating needs, including model access, data protection, cost attribution, auditability, workload classification, sandboxing, governed knowledge, and AI governance.
Technical fluency with cloud platforms, AI platforms, platform engineering, or enterprise architecture.
Demonstrated ability to use AI tools as a practical system-building accelerator for analysis, documentation, planning, technical review, or lightweight prototyping.
Ability to translate technical platform work into business outcomes, stakeholder decisions, funding needs, and adoption measures.
Proven experience working across senior stakeholders in technology, security, privacy, compliance, finance, legal, architecture, product, and delivery organizations.
Strong written communication skills, including decision memos, roadmap artifacts, and operating model documentation.

Nice To Haves

Experience with AWS, Amazon Bedrock, enterprise AI platforms, MLOps, LLMOps, platform engineering, or cloud governance.
Experience with durable agentic AI orchestration platforms for platform, business, or AI operational workflows.
Experience creating or operating intake, prioritization, governance, exception, or architecture review processes.
Experience with regulated, client-sensitive, PHI, PII, or confidential-data environments.
Experience leading platform adoption across federated business teams.

Responsibilities

Hire, develop, and manage the AI Infrastructure Operations team, including architects and engineers; set goals, provide coaching and performance feedback, and build team capability over time.
Own day-to-day execution of the AI Infrastructure Operations charter: roadmap delivery, prioritization, intake process, decision forums, adoption outcomes, and operating cadence.
Operate the governed enterprise AI capability, including workload classes, priority use cases, Bedrock access needs, usage and cost visibility, sandbox ownership, application and agent registration, logging, exception handling, Huron Knowledge validation, and decision rights.
Run the federated platform operating model in partnership with Client-facing AI Delivery, Enterprise IT, Global Products, Engineering, Analytics, Consulting, Security, Privacy, Compliance, Legal, Finance, and Enterprise Architecture.
Partner with the AI Capability Center under the Chief AI Officer to align priorities, innovate, and deliver the infrastructure and platform capabilities behind solutions for Huron's go-to-market teams.
Provide enough technical direction, working with the AI Infrastructure Architect, to make architecture, sequencing, control-plane, and delivery tradeoffs visible and actionable.
Use AI tools to accelerate planning, documentation, backlog development, decision records, stakeholder communication, and review of platform artifacts.
Ensure AI Operations is positioned as an enablement capability that provides reusable, approved, observable, and cost-managed paths for AI adoption.
Manage scope, stakeholder participation, budget tracking, and scaling criteria across delivery phases.
Track and report success measures for governed access adoption, workload visibility, cost visibility, operational readiness, Huron Knowledge enablement, agent safety, and delivery acceleration.