AI FinOps / AI Cost Optimization Consultant

We are looking for an experienced AI FinOps / Cloud Cost Optimization Consultant with strong expertise in AI/ML workloads, cloud financial management, and cost reduction. The ideal candidate will help organizations understand, monitor, optimize, and reduce the costs associated with cloud infrastructure, data platforms, and generative AI workloads.

The candidate should have a strong combination of AI knowledge, cloud architecture understanding, FinOps, financial analysis, and business problem-solving skills. The primary objective is to identify opportunities to reduce technology and AI spending while maintaining performance, scalability, reliability, and business value.

Key Responsibilities

• Develop and implement FinOps strategies for AI/ML and cloud environments.
• Analyze and optimize costs associated with Generative AI, LLMs, GPU/CPU workloads, APIs, model inference, training, and data processing.
• Identify opportunities to reduce cloud and AI expenses without negatively impacting application performance or business requirements.
• Analyze cloud spending trends, usage patterns, resource utilization, and cost drivers.
• Build cost optimization models, dashboards, forecasts, and reporting for AI and cloud environments.
• Establish cost allocation, tagging, chargeback/showback, and unit-cost measurement strategies.
• Analyze AI workloads and recommend appropriate model selection, infrastructure sizing, compute options, and deployment strategies based on cost and performance.
• Optimize LLM usage through techniques such as model selection, prompt optimization, token reduction, caching, batching, and workload routing.
• Identify underutilized or unnecessary cloud resources and recommend rightsizing, scheduling, reserved capacity, or other optimization strategies.
• Partner with Cloud, DevOps, Data Engineering, AI/ML, Finance, and Engineering teams to drive measurable cost reductions.
• Develop AI cost forecasting and budgeting models to support future growth.
• Establish KPIs such as cost per request, cost per token, cost per inference, cost per customer, and cost per workload.
• Monitor actual savings and validate that optimization initiatives deliver the expected financial benefits.
• Automate cost monitoring, anomaly detection, and optimization recommendations where possible.
• Evaluate the financial impact of new AI initiatives before production implementation.
• Present cost optimization opportunities and recommendations to senior management and business stakeholders.

Required Skills

• Strong experience with FinOps and Cloud Cost Optimization.
• Hands-on experience with AI/ML and Generative AI technologies.
• Strong understanding of LLMs, AI inference, model training, GPU workloads, APIs, and token-based pricing.
• Experience with one or more major cloud platforms:
• AWS
• Microsoft Azure
• Google Cloud Platform (Google Cloud Platform)
• Experience with cloud cost-management tools such as AWS Cost Explorer, Azure Cost Management, Google Cloud Billing, or similar platforms.
• Strong understanding of cloud architecture and resource utilization.
• Experience analyzing large-scale technology spending and identifying cost-reduction opportunities.
• Strong SQL and data-analysis skills.
• Experience creating dashboards using Power BI, Tableau, Looker, or similar tools.
• Strong Excel/financial modeling skills.
• Knowledge of cloud pricing models, reservations, savings plans, committed-use discounts, and resource rightsizing.
• Strong communication and stakeholder-management skills.
• Ability to translate complex technical costs into business and financial recommendations.