Manager- On-Premises, Cloud & AI Agent FinOps

Title: Manager- On-Premises, Cloud & AI Agent FinOps

Location: Newton Square, PA (hybrid, 3 days onsite every week)

Duration: Contract to hire after 3-6 months

Position Summary:

The Manager, On-Premises, Cloud & AI Agent FinOps is responsible for establishing and leading financial governance, cost optimization, and operational management of hybrid IT infrastructure environments, including on-premises data centers, public cloud platforms, and AI-powered agent ecosystems.

This leadership role partners with Infrastructure, Cloud Engineering, Platform Engineering, Enterprise Architecture, Finance, Security, Compliance, Procurement, and Business stakeholders to ensure technology investments deliver measurable business value while maintaining financial accountability, governance, and regulatory compliance.

The manager will oversee enterprise FinOps practices, AI Agent Governance, technology budgeting, forecasting, show back/chargeback reporting, cost transparency initiatives, and financial optimization across cloud, on-premises, and AI-driven services.

Primary Responsibilities:

FinOps Strategy & Financial Management:

• Develop and mature enterprise FinOps capabilities across cloud and on-premises infrastructure.
• Create financial visibility into compute, storage, networking, backup, virtualization, licensing, and platform services.
• Lead technology budget planning, forecasting, and variance analysis.
• Establish showback and chargeback models for business units and shared services.
• Manage cloud consumption costs and identify rightsizing opportunities.
• Create executive dashboards and financial reports for leadership.
• Partner with Finance and Procurement on contract reviews, renewals, and vendor negotiations.
• Drive continuous cost optimization initiatives across infrastructure platforms.

On-Premise Infrastructure Financial Governance:

• Maintain cost transparency for data center resources including servers, storage, backup, virtualization, and network services.
• Develop unit-cost metrics and capacity-based financial models.
• Analyze utilization trends and identify opportunities to reduce stranded capacity.
• Support infrastructure lifecycle planning and capital investment decisions.
• Evaluate infrastructure modernization opportunities to reduce operational costs.

Cloud Financial Operations:

• Manage financial governance across Azure, AWS, and SaaS services.
• Implement tagging, allocation, and cost attribution standards.
• Monitor cloud spend and consumption trends.
• Develop forecasting models and budget projections.
• Lead cloud cost optimization programs including:
  • Rightsizing
  • Reservation strategies
  • Savings plans
  • Storage optimization
  • Workload placement decisions

AI Agent Governance & Financial Oversight:

• Establish and manage the enterprise AI Agent Governance framework.
• Maintain inventories of approved AI agents, copilots, and intelligent automation solutions.
• Develop governance processes for AI lifecycle management.
• Partner with Security, Legal, Compliance, and Data Governance teams to ensure Responsible AI adoption.
• Monitor AI usage, token consumption, model costs, and platform utilization.
• Implement financial accountability and chargeback models for AI platforms and services.
• Evaluate ROI and business value of AI investments.
• Define governance controls for AI risk, privacy, security, and regulatory compliance.

Reporting & Analytics:

• Develop executive-level dashboards and KPIs.
• Measure cloud, infrastructure, and AI financial performance.
• Track savings opportunities and cost avoidance initiatives.
• Provide financial recommendations to senior leadership.
• Utilize Power BI, analytics platforms, and FinOps tooling to create actionable insights.

Vendor & Tool Management:

• Evaluate and manage FinOps, ITFM, and AI governance platforms.
• Lead vendor assessments, RFPs, and technology evaluations.
• Manage strategic partner relationships.
• Ensure technology investments align with business objectives and financial goals.

Leadership & Team Management:

• Foster a culture of accountability, innovation, and continuous improvement.
• Collaborate across Infrastructure, Security, Cloud Operations, Platform Engineering, and Finance teams.
• Present financial and governance recommendations to executive leadership.

Required Qualifications:

Education:

• Bachelor's degree in Information Technology Computer Science, Finance, Accounting, Business Administration, or related field.

Experience:

• 8-12 years of experience in IT Infrastructure, Cloud Operations, Financial Management, FinOps, or Platform Engineering.
• 3-5 years of leadership or management experience.
• Experience managing hybrid cloud and on-premises environments.
• Experience with budgeting, forecasting, and financial planning.
• Experience implementing FinOps practices and governance frameworks.
• Experience with AI, automation, Copilot, or AI Agent platforms preferred.

Technical Skills:

Cloud Platforms:

• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (Preferred)

Infrastructure Technologies:

• VMware vSphere / ESXi
• Storage Platforms
• Backup & Recovery Solutions
• Networking & Data Center Technologies

FinOps & Financial Management:

• Budget Planning
• Forecasting
• Chargeback / Showback
• Cost Allocation
• Cost Optimization
• Technology Financial Management (TBM/ITFM)

AI & Governance:

• Microsoft Copilot
• Azure AI Services
• AI Agent Governance Frameworks
• Responsible AI Controls
• Data Governance
• AI Risk Management

Analytics & Reporting:

• Power BI
• Excel
• Financial Modeling
• Dashboard Development
• Executive Reporting

Preferred Certifications:

Cloud:

• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure Administrator Associate
• AWS Certified Solutions Architect

FinOps:

• FinOps Certified Practitioner
• FinOps Certified Professional

AI:

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Applied Skills for Copilot and AI Solutions

Success Measures:

• Improved cloud and infrastructure cost transparency
• Annual cost savings and optimization targets achieved
• Accurate budget forecasting and variance management
• Successful implementation of AI governance controls
• Increased accountability through showback/chargeback models
• Executive adoption of financial and operational reporting
• Demonstrated ROI from AI and cloud investments