Vice President, Intelligent Automation & IT Operations

Vice President Of Intelligent Automation & It Operations

Working across the globe, V2X builds smart solutions designed to integrate physical and digital infrastructure from base to battlefield. We bring 120 years of successful mission support to improve security, streamline logistics, and enhance readiness. Aligned around a shared purpose, our $3.9B company and 16,000 people work alongside our clients, here and abroad, to tackle their most complex challenges with integrity, respect, responsibility, and professionalism.

Responsibilities

The Vice President of Intelligent Automation & It Operations is the senior technology executive responsible for designing and operating the organization's AI-first IT operational environment. This leader will build and govern the greenfield IT infrastructure, automation platforms, endpoint ecosystem, and network fabric that collectively form the foundation for an enterprise AI Fabric running on a modern Data Fabric. Reporting to the CIO, the VP will lead a blended human-AI team, drive the deliberate reinvention of IT operations from legacy, human-managed processes to AI-driven operations with human oversight, and serve as the internal authority on AIOps strategy, agent governance, and AI-ready infrastructure. This role is the architect of the organization's journey from Pre-AI IT to AI-First IT — as defined by Gartner's IT 2030 framework.

Key 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 and own 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.
• Maintain strategic vendor relationships with SASE, UEM, AIOps, and AI platform providers, ensuring the organization benefits from AI-native product roadmaps.

• Ensure all IT systems, automation frameworks, and AI agents operate in compliance with CMMC Level 2, NIST 800-171, and applicable federal regulations.
• Partner with the CISO to extend the Zero Trust architecture to AI agents and automated workloads — ensuring machine identity, least-privilege access, and continuous verification apply to non-human actors.
• Oversee AI risk management: adversarial prompt injection defense, model drift monitoring, AI-generated threat detection, and governance of AI tools used within the IT environment.
• Provide board- and executive-level reporting on IT operational health, AI adoption maturity, compliance posture, and strategic roadmap progress.
• Ensure audit readiness across all IT domains, with AI-augmented continuous monitoring reducing the manual burden of compliance evidence collection.

• Build, lead, and develop a high-performing team spanning network, endpoint, automation, and AI platform engineering disciplines.
• Foster a psychologically safe, learning-oriented culture where experimentation with AI tools is encouraged and failure is treated as a data point.
• Define career ladders and growth paths that account for the evolving human-AI blended workforce model, including AI-augmented roles that will emerge as automation matures.
• Recruit and retain top technical talent by creating an environment where engineers work on genuinely novel AI-first infrastructure problems.
• Represent IT Intelligent Automation and Operations in cross-functional leadership forums, translating technical strategy into business value for non-technical executives.

Qualifications

Minimum Qualifications:

• Bachelor's degree in Information Technology, Computer Science, Engineering, or related field required.

Experience

• 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.
• Experience with FedRAMP-authorized cloud and AI platform environments

Other Requirements

• Ability to travel to project and customer locations.
• U.S. Citizenship required
• Ability to obtain and maintain a security clearance

Preferred Requirements

• Master's degree in a technical or business discipline strongly preferred.
• ITIL, PMP, or equivalent program/portfolio management certification preferred.
• Familiarity with Gartner IT research and AI-First IT frameworks preferred.
• 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.

Skills

• Ability to present AI strategy and IT operational roadmaps at executive and board level.
• Deep expertise in AI-First IT strategy, AIOps platforms, and intelligent automation frameworks.
• Strong understanding of AI agent governance models, machine identity management, and human-in-the-loop design patterns.
• Excellent executive communication and storytelling skills — able to translate complex AI and infrastructure strategy into business outcomes.
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