FinOps AI & Optimization Practitioner
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IT/Tech
AI Business & Operations, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
Make an impact with NTT DATA
Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive.
Your day at NTT DATA
The Fin Ops AI & Optimization Practitioner will enable financial transparency, accountability, and optimization across cloud, on-premises, and AI services. The role will help the organization understand, govern, forecast, and optimize consumption across traditional infrastructure and emerging AI workloads, including token-based services, GPU-intensive workloads, AI platforms, and SaaS-based AI capabilities.
The mission is to drive cost-efficient and accountable technology adoption by aligning usage, performance, risk, and business value. The Fin Ops AI & Optimization Practitioner collaborates closely with engineering, finance, procurement, operations, product teams, and business stakeholders to embed Fin Ops practices into daily decision-making and support scalable, responsible AI adoption.
This position is based in Veldhoven, Netherlands and follows a hybrid working model requiring office presence three days per week.
Key Responsibilities- Drive cost optimization across cloud, on-premises, SaaS, and AI services by identifying savings opportunities, validating business impact, and supporting implementation with accountable owners.
- Establish Fin Ops for AI practices covering AI cost visibility, allocation, forecasting, budgeting, anomaly detection, unit economics, cost-per-token, cost-per-inference, GPU utilization, and AI business value tracking.
- Proactively equip, guide, and train stakeholders on Fin Ops, cloud optimization, and AI cost management practices through the Community of Practice.
- Ensure reliable cost management tooling, including access control, data quality, cost mapping, tagging/labeling standards, dashboards, reporting, and vendor engagement for improvements.
- Identify, analyze, and report cost opportunities and risks across Azure, Google Cloud, on-premises, and AI consumption; partner with stakeholders to remediate actions and track benefits.
- Manage commitment-based savings instruments such as reservations, committed use discounts, savings plans, and AI/GPU capacity commitments in alignment with workload demand and risk.
- Support budgeting, forecasting, showback, chargeback, and business case creation for cloud migration, workload modernization, and AI initiatives.
- Define and track KPIs that improve accountability and value realization, including spend variance, forecast accuracy, optimization execution, workload efficiency, AI unit costs, and realized savings.
- Collaborate with internal teams and external providers to understand pricing models, SKU changes, capacity constraints, licensing impacts, and optimization levers.
- Stay current with Fin Ops, cloud pricing, AI service pricing, GPU infrastructure, token-based consumption, sustainability, and industry best practices.
- Minimum 5 years of experience in Fin Ops, cloud cost management, IT finance, cloud operations, platform engineering, or a related role in an international IT organization.
- Strong understanding of Azure and Google Cloud cost models, cloud principles, reservations/commitments, tagging, allocation, forecasting, budgeting, showback, and chargeback.
- Experience translating technical usage into financial insights and actionable recommendations for non-finance stakeholders and business owners.
- Experience with cost visualization and analytics tools; ability to create dashboards, reports, and insights that support decisions.
- Experience with change…
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