Cloud & AI FinOps Engineer

Sr Cloud Engineer - IE07NE We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

Overview The Enterprise Cloud Services team supports The Hartford’s multi-cloud transformation by providing a robust, optimized, self-service cloud experience that enables business value for our customers. The FinOps Center of Enablement partners across technology, finance, product, and business teams to strengthen financial accountability and maximize the value of cloud investments. The Cloud & AI FinOps Analyst is an onshore, hands-on role that blends cloud engineering knowledge, financial analysis, data analytics, automation, and stakeholder consulting. This individual will turn cloud and AI consumption data into actionable insights, improve forecasting and allocation, identify and help deliver optimization opportunities, and mature FinOps practices across the enterprise. The role partners with application owners, engineers, architects, product teams, finance, procurement, and leadership, with primary depth in AWS, strong working knowledge of GCP, and familiarity with Azure cost-management concepts.

Cloud Cost Management and Optimization Administer and improve cloud financial management platforms, including IBM Apptio Cloudability, AWS native cost tools, and applicable GCP or Azure capabilities. Monitor cloud and AI cost and usage trends; investigate anomalies, billing discrepancies, unallocated spend, and material forecast variances; and coordinate root-cause analysis and corrective action. Build a prioritized optimization pipeline covering rightsizing, idle-resource cleanup, storage lifecycle, workload scheduling, architecture changes, and service-selection tradeoffs; track recommendations through implementation and validate realized savings. Analyze and manage commitment-based discount opportunities, including AWS Savings Plans and Reserved Instances, Spot, and GCP committed use discounts; monitor coverage, utilization, break-even points, and financial risk. Partner with architects, cloud engineers, reliability engineers, developers, product teams, and application owners to embed cost, performance, reliability, and sustainability considerations into design and capacity decisions. Develop cost estimates, unit-cost models, and scenarios for workloads migrating to, scaling within, or modernizing in the cloud. Apply AI-assisted analytics and automation to anomaly detection, forecasting, recommendation prioritization, and narrative reporting, while validating outputs and maintaining appropriate data, security, and governance controls. Financial Planning, Reporting, and Analytics Support monthly, quarterly, and annual budget and forecast cycles for cloud and AI services, including consumption, show back or chargeback, savings, commitment, and demand planning. Develop and improve trusted reports, dashboards, forecasts, alerts, and executive-ready insights using standardized cost and usage data. Analyze large and complex datasets, build financial and unit-economics models, and translate technical cost drivers into clear recommendations and business tradeoffs. Perform variance analysis and maintain month-end and quarter-end reporting, operational metrics, usage statistics, and KPI or OKR measures. Establish and track metrics such as forecast accuracy, allocation coverage, commitment utilization, realized savings, optimization adoption, cost per transaction, cost per customer or product, and—where applicable—cost per token, inference, model, or AI workload. Help cloud consumers understand their bills, cost drivers, efficiency trends, business impact, and options for aligning consumption with goals and budgets. Produce concise management reporting that distinguishes