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Air Canada is seeking a Specialist, Cloud and AI FinOps to support the financial management, optimization, governance, and operation of our growing enterprise Artificial Intelligence and cloud ecosystem. This role will have a strong focus on AI FinOps and Cloud Financial Management, helping Air Canada understand, forecast, optimize, and govern investments across cloud and enterprise AI platforms. This includes Large Language Models (LLMs), Generative AI applications, AI agents, consumption-based AI services, and enterprise AI licensing.
A key aspect of the position will be establishing visibility into both the cost and business value of AI adoption. The Specialist will help develop financial models, forecasts, dashboards, and Return on Investment (ROI) assessments that enable technology and business leaders to make informed decisions regarding AI investments.
The role will also support the administration and operation of enterprise AI platforms and provide operational support for selected DevOps platforms. The ideal candidate combines strong FinOps, financial analysis, cloud cost management, and data analytics capabilities with a practical understanding of enterprise AI platforms, AWS, Generative AI consumption models, licensing, and platform operations.
Responsibilities:
AI Consumption & Cost Optimization
- Monitor, analyze, and optimize AI-related expenditures across enterprise AI platforms and services.
- Track LLM token consumption, inference requests, API usage, model utilization, licensing, and associated infrastructure costs.
- Analyze AI consumption trends across applications, projects, business units, and users to identify optimization opportunities.
- Evaluate the financial efficiency of AI models using metrics such as cost per token, cost per request, utilization, and cost-performance trade-offs.
- Identify opportunities to optimize AI expenditure through appropriate model selection, usage patterns, licensing, and consumption controls.
- Monitor costs associated with AI agents, agentic workflows, and multi-model AI applications.
- Analyze enterprise AI license utilization and identify opportunities to improve allocation and reduce unused or underutilized capacity.
- Partner with AI, application development and other teams to promote cost-effective AI consumption practices.
Cloud Cost Management & Optimization
- Monitor and analyze AWS cloud expenditures across accounts, applications, and business units.
- Identify cost optimization opportunities including resource rightsizing, unused resources, storage optimization, and improved consumption efficiency.
- Analyze AWS consumption patterns and provide actionable recommendations to improve cloud financial efficiency.
- Support the optimization of AWS Savings Plans, Reserved Instances, and other cloud pricing commitments.
- Partner with DevOps, SRE, application, infrastructure, and cloud teams to implement cost optimization initiatives.
- Track and report realized savings, cost avoidance, and financial benefits generated through optimization activities.
Budgeting, Forecasting & Financial Planning
- Support annual and ongoing cloud and AI budget planning, forecasting, and expenditure management.
- Analyze historical spending, consumption patterns, and adoption trends to develop financial projections.
- Develop and maintain forecasts for enterprise AI platforms, cloud services, licensing, and related technology investments.
- Monitor actual spending against budgets and forecasts and investigate material variances.
- Develop financial dashboards and executive-level reporting highlighting expenditure, consumption trends, financial risks, and optimization opportunities.
- Partner with Finance and technology stakeholders to improve financial accountability and expenditure visibility.
- Develop financial models to estimate the cost of new AI use cases, applications, platform adoption, and infrastructure expansion.
- Provide cost projections and financial insights to support cloud and AI investment decisions.
AI Investment Analysis & ROI
- Develop and maintain ROI assessments for enterprise AI platforms, services, and initiatives.
- Partner with Finance, business units, and technology stakeholders to evaluate the business and financial value generated by AI investments.
- Work with different teams to establish metrics to measure AI investment performance, including cost savings, productivity improvements, operational
efficiencies, utilization, and measurable financial benefits. - Support business cases and financial justification for new AI initiatives and platform investments.
- Compare actual AI expenditures with expected and realized benefits to assess investment effectiveness.
- Develop dashboards and executive reporting that provide visibility into AI investment performance.
- Identify underutilized or low-value AI investments and recommend opportunities to improve financial returns.
- Partner with business owners to validate realized benefits and differentiate measurable financial savings from estimated productivity improvements.
- Provide financial insights to help prioritize AI investments and maximize business value.
AI Financial Governance
- Develop and maintain cloud and AI cost dashboards for technical teams, management, Finance, and business stakeholders.
- Establish cost allocation and reporting practices across AI applications, projects, departments, and business units.
- Support showback and chargeback models for cloud and AI consumption.
- Define and monitor AI financial KPIs such as cost per user, application, request, model, and token.
- Implement and maintain budgets, spending thresholds, alerts, and anomaly detection where supported by the applicable platforms.
- Investigate unexpected changes in AI and cloud consumption and assess their financial impact.
- Support AI financial governance policies, consumption standards, and cost management practices.
- Support cloud tagging and allocation standards to improve financial accountability.
AI Licensing, Cost Management & Operations
- Monitor and optimize enterprise AI licensing, subscriptions, and consumption-based services.
- Analyze licensing utilization and adoption across platforms different platforms.
- Support financial evaluations of AI service providers, pricing models, licensing structures, and commercial agreements.
- Partner with Procurement, Finance, technology, security teams, and vendors to support contract renewals and consumption commitments.
- Identify opportunities to improve licensing efficiency and reduce unnecessary expenditure.
- Provide financial analysis to support AI platform renewals, expansions, and licensing decisions.
- Support AI security controls, access management, governance, and compliance requirements.
- Coordinate with technology vendors and internal stakeholders to continuously improve platform operations.
- Partner with architecture, cybersecurity, infrastructure, and engineering teams to support scalability, reliability, performance, security, and governance
requirements. - Administer platform configurations, user access, groups, licensing, service availability, and integrations.
- Monitor LLM performance, latency, throughput, token utilization, availability, and consumption.
- Support model selection, version management, and platform configuration.
DevOps Platform Support
- Minimum 5 years of relevant experience in FinOps, Cloud Financial Management, IT Financial Management, AI platform operations, cloud platform operations, or a related field.
- Strong experience in financial analysis, budgeting, forecasting, cost management, and optimization of cloud or technology services.
- Practical experience with AWS cloud financial management and cost analysis tools.
- Strong understanding of cloud consumption, pricing, billing, cost allocation, and optimization concepts.
- Understanding of Generative AI, Large Language Models, AI consumption models, and consumption-based AI pricing.
- Knowledge of token-based pricing, inference consumption, subscription models, and enterprise AI licensing.
- Experience analyzing large volumes of cloud or technology consumption data and translating findings into actionable recommendations.
- Experience developing financial dashboards, forecasts, cost reports, and executive-level financial insights.
- Experience with ROI assessments, business case analysis, investment analysis, or financial benefit tracking.
- Familiarity with enterprise AI services such as Amazon Bedrock, Anthropic Claude, GitHub Copilot, or comparable platforms.
- Strong knowledge of Excel and experience with analytical or visualization tools.
- Strong analytical and problem-solving capabilities with the ability to connect technical consumption data to financial and business outcomes.
- Strong written and verbal communication skills, including the ability to communicate financial and technical information to different audiences.
- Ability to collaborate across Finance, Procurement, Cloud, DevOps, SRE, Data & AI, Cybersecurity, architecture, engineering, and business teams.
- Applies financial acumen and analytical thinking to optimize technology investments, forecast costs, and enable data-driven decision making.
- Collaborates effectively with business and technology leaders, influencing stakeholders and communicating insights to executive audiences.
- Drives operational excellence through strong problem solving, attention to detail, accountability, and a focus on continuous improvement.
- Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.
Assets
- FinOps Certified Practitioner, FinOps Certified Professional, or equivalent experience.
- AWS certification such as AWS Certified Cloud Practitioner or AWS Certified Solutions Architect.
- Experience managing AI-related expenditures in a large enterprise environment.
- Experience with Anthropic Claude enterprise licensing, administration, or usage analytics.
- Experience with GitHub Copilot administration, licensing, seat utilization, or adoption analytics.
- Familiarity with Amazon Bedrock pricing, model usage, inference consumption, and cost management.
- Understanding of AI agents, agentic workflows, AI gateways, and multi-model architectures.
- Experience with AWS Organizations, consolidated billing, Savings Plans, and Reserved Instances.
- Experience with AWS Cost Explorer, AWS Budgets, Cost and Usage Reports, Cost Anomaly Detection, Amazon Athena, SQL, or similar analytics capabilities.
- Experience implementing cloud financial governance, showback, or chargeback models.
- Experience measuring AI productivity improvements, operational efficiencies, or financial returns.
- Familiarity with GitHub, Harness, CI/CD concepts, and enterprise DevOps platforms.
- Familiarity with Python, Terraform, Infrastructure as Code, or automation concepts.
Conditions of Employment:
Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.
Linguistic Requirements
Based on equal qualifications, preference will be given to bilingual candidates.
Diversity and Inclusion
Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.
As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.
Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.
