AI FinOps Consultant at Slalom, LLC in Denver, Colorado

Finops For Ai Practitioner Consultant

You'll join a consulting team that helps clients manage, optimize, and govern the financial value of cloud, AI, and data investments. You'll work alongside FinOps strategists, cloud architects, data and AI practitioners, finance leaders, engineering teams, product owners, and client executives to help organizations build practical FinOps capabilities for AI-enabled environments. You'll support clients who are adopting or scaling AI solutions, including generative AI, machine learning platforms, AI-enabled applications, data platforms, and cloud-native services. Your work will help clients improve cost transparency, strengthen accountability, optimize usage, and connect AI investments to measurable business outcomes.

As a FinOps for AI Practitioner Consultant, you will help clients apply FinOps principles to cloud and AI investments, with a focus on visibility, accountability, optimization, and value realization.

• Assess client cloud, AI, and data cost management practices, identifying maturity gaps, risks, and opportunities.
• Help design and implement FinOps operating models, governance processes, reporting structures, and decision frameworks.
• Analyze cloud, AI, and platform consumption patterns to identify cost drivers, optimization opportunities, and value improvement levers.
• Support AI-specific FinOps use cases, including model usage tracking, token and inference cost analysis, GPU and accelerator cost management, experimentation controls, chargeback/showback, and AI unit economics.
• Partner with engineering, product, finance, and business stakeholders to connect technical consumption data to business value.
• Develop dashboards, reports, and executive-ready insights that explain cost, usage, performance, and value trends.
• Help clients define KPIs, tagging standards, allocation models, budgets, forecasts, and anomaly management processes.
• Facilitate workshops with client stakeholders to align on FinOps practices, roles, responsibilities, and adoption roadmaps.
• Support optimization initiatives across cloud infrastructure, AI platforms, data workloads, vendor services, and usage patterns.
• Translate FinOps Foundation frameworks and best practices into practical recommendations tailored to each client's environment.
• Contribute to consulting offerings, reusable assets, playbooks, accelerators, and thought leadership related to FinOps for AI.
• Stay current with emerging FinOps for AI and Tokenomics practices, pricing models, optimization techniques, and the FinOps Foundation framework.

You have 3+ years' experience supporting FinOps, cloud cost management, cloud governance, technology finance, IT financial management, or related consulting work.

• Understanding FinOps principles, including cost visibility, allocation, budgeting, forecasting, optimization, accountability, and value management.
• Familiarity with public cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Awareness of AI, machine learning, generative AI, data platforms, and AI-enabled application architectures.
• Strong understanding of AI cost drivers and architecture patterns, including token-based pricing, GPU utilization, inference costs, model hosting, caching, vector databases, Retrieval-Augmented Generation (RAG), Cache-Augmented Generation (CAG), prompt engineering, model routing, and how these choices impact cost, performance, scalability, and business value.
• Ability to analyze usage, cost, and performance data to identify trends, risks, and opportunities.
• Knowledge of cloud billing, cost allocation, and usage data structures, including an understanding of the FOCUS format and its role in normalizing cloud cost and usage data across providers and tools.
• Ability to work with normalized cost and usage datasets to support reporting, allocation, unit economics, forecasting, and optimization analysis.
• Strong communication skills, with the ability to explain technical and financial concepts to executive, finance, engineering, and product audiences.
• Experience creating client-facing deliverables such as assessments, roadmaps, business cases, dashboards, executive summaries, and operating model recommendations.
• Comfort facilitating stakeholder conversations, workshops, and working sessions.
• Ability to work in ambiguous environments and structure complex problems into clear recommendations.
• A practical, outcome-oriented mindset focused on helping clients improve financial accountability and business value from technology investments.

Preferred Experience

• FinOps Foundation certification, especially: FinOps Certified Practitioner FinOps Certified AI Value
• Experience working with the FOCUS format or other cloud cost and usage data standards to normalize, analyze, and report on multi-cloud or multi-platform spend.
• Experience mapping native billing exports from AWS, Azure, Google Cloud, SaaS platforms, AI platforms, or third-party FinOps tools into standardized cost and usage models.
• Experience with cloud cost management tools or native billing platforms, such as AWS Cost Explorer, AWS CUR, Azure Cost Management, Google Cloud Billing, CloudHealth, Apptio Cloudability, Flexera, Harness, or similar platforms.
• Experience with AI or GenAI cost management, including token consumption, model selection, inference costs, GPU utilization, prompt/application cost attribution, or AI value tracking.
• Experience designing showback, chargeback, unit cost, or cost allocation models.
• Experience developing FinOps dashboards using tools such as Power BI, Tableau, Looker, Excel, or cloud-native reporting tools.
• Experience working with engineering teams on optimization efforts such as rightsizing, reserved capacity, savings plans, workload scheduling, storage optimization, model efficiency, or platform governance.
• Knowledge of AI platforms and services such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenAI APIs, Databricks, Snowflake, or Kubernetes-based AI workloads.
• Consulting experience in cloud transformation, data and AI strategy, platform modernization, technology operating models, or enterprise cost optimization.
• Experience helping organizations establish FinOps teams, governance forums, policies, standards, and adoption roadmaps.
• Familiarity with responsible AI, AI governance, data governance, or risk management practices.