Vice President, Intelligent Automation & IT Operations

Responsibilities

• Define and own the organization’s AI-First IT strategy, establishing deliberate reinvention programs, milestones, and success metrics aligned to the Gartner AI-First IT framework.
• Lead the greenfield IT build: architect the clean, modern, automated operational environment in parallel with the brownfield, then orchestrate deliberate workload migration and legacy SaaS sunset.
• Establish the application rationalization workstream with defined criteria, triggers, and timelines for decommissioning legacy SaaS applications as AI-native replacements mature.
• Serve as the executive sponsor for the enterprise AI Fabric and Data Fabric integration, ensuring IT infrastructure is purpose-built to support AI model serving, agentic workloads, and intelligent data pipelines.
• Maintain a forward-looking technology radar informed by Gartner research, industry analyst insights, and emerging AI-native vendor ecosystems to continuously evolve the IT strategy.
• Establish the enterprise AI agent governance framework: define authorization models, human-in-the-loop thresholds, audit trails, and escalation paths for AI agents operating within IT systems.
• Define the roles and responsibilities of AI agents as stakeholders within IT operations — including agent identity management, permission scoping, and behavioral monitoring.
• Lead the organization’s transition to a blended human-AI workforce model, including workforce planning, role redefinition, change management, and AI literacy programs for IT staff.
• Partner with HR, Legal, and the CISO to develop policies governing AI agent use, data access, and decision authority within the IT operational environment.
• Champion a culture of automation-first and AI-augmented decision-making across all IT functions, ensuring staff are equipped and motivated to work alongside intelligent systems.
• Oversee the design and operation of the AIOps platform, ensuring AI-driven incident detection, automated triage, closed-loop remediation, and predictive operations across all IT domains.
• Drive the evolution from script-based automation to agentic operations — where AI agents autonomously execute multi-step operational workflows with appropriate human oversight.
• Establish KPIs for intelligent operations including MTTR reduction, automation coverage, agent action accuracy, and operational toil elimination.
• Own the integration architecture connecting AIOps, ITSM, observability, and the AI Fabric — ensuring all IT operational data flows into the intelligence layer that powers continuous improvement.
• Govern the CI/CD and Infrastructure-as-Code practices across all teams, ensuring automation quality, security, and auditability.
• Evaluate and manage an increasingly diverse ecosystem of AI-native vendors, distinguishing between proven enterprise solutions and emerging AI-native alternatives across all IT domains.
• Negotiate new consumption models — outcome-based, usage-based, and agent-consumption pricing — as AI-native vendors displace traditional licensing structures.
• Own AI infrastructure cost governance: GPU and inference compute cost modeling, AI ROI measurement, and FinOps practices for AI workloads including automated rightsizing and spend alerting.
• Build the business case for IT investment in AI Fabric capabilities, translating AI operational metrics into executive-level narratives on capacity expansion, risk reduction, and competitive positioning.
• Represent IT Intelligent Automation and Operations in cross-functional leadership forums, translating technical strategy into business value for non-technical executives.

Qualifications

• Bachelor’s degree in Information Technology, Computer Science, Engineering, or related field required.
• A minimum of twenty (20) years of progressive experience in IT operations, infrastructure, or engineering.
• A minimum of seven (7) years in a senior leadership role with direct management of technical teams and budgets.
• Demonstrated experience leading a greenfield or large-scale IT transformation program.
• Proven track record of implementing AIOps, intelligent automation, or AI-driven operational platforms at enterprise scale.
• Experience establishing AI agent governance frameworks or human-AI workforce models strongly preferred.
• Hands-on familiarity with Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP), and Zero Trust architecture.
• Experience in the government contractor/services industry required.
• Experience with obtaining and maintaining an organizational CMMC Level 2 certification required.
• Ability to travel to project and customer locations.
• U.S. Citizenship required.
• Active Secret security clearance desired.
• Demonstrated experience with FinOps for AI infrastructure, including GPU cost modeling and inference spend optimization.
• Prior experience operating in a DoD or federal contractor environment.