Senior FinOps Product Engineer

• Contribute to the FinOps product vision, roadmap, backlog, and measurable outcomes across DPTs, translating strategy into prioritized capabilities and user experiences.
• Partner with product, engineering, platform, finance, architecture, and data stakeholders to identify user needs, define requirements, manage tradeoffs, and drive adoption.
• Define success measures for FinOps capabilities, including adoption, forecast accuracy, unit-cost improvement, optimization realization, and engineering engagement.
• Assist application areas define and operationalize unit economics such as cost per quote, claim, policy, transaction, workload, customer interaction, AI inference, or other business-relevant unit.
• Connect technology consumption and product costs to business outcomes through consistent allocation models, product metadata, and value-oriented KPIs.
• Create frameworks and reusable data products that enable DPTs to compare unit-cost trends, understand cost drivers, and evaluate architectural or product decisions.
• Collaborate with stakeholders to establish AI cost governance across model usage, token consumption, inference, training, fine-tuning, agentic workflows, and supporting data or platform services.
• Develop tokenomics and AI unit-cost measures, including cost per token, request, inference, user interaction, agent task, or business outcome.
• Enable model-selection economics by evaluating cost, performance, quality, latency, capacity, and business-value tradeoffs.
• Drive optimization opportunities through prompt efficiency, context and cache management, right-sized model selection, capacity planning, and managed commitment strategies.
• Deliver actionable intelligence on utilization, cost trends, anomalies, and optimization opportunities across AWS, Azure, GCP, and hybrid environments.
• Optimize containerized workloads by improving Kubernetes cluster efficiency, node and pod rightsizing, autoscaling, scheduling, idle-capacity management, storage and network consumption, and shared-cost allocation.
• Identify and facilitate savings through workload modernization, rightsizing, scheduling, licensing strategies, commitment programs, reservations, and vendor negotiations.
• Oversee cloud billing and enterprise discount programs, including Savings Plans, Reserved Instances, reservations, and other commitment-based constructs.
• Embed cost insight and policy into engineering workflows such as CI/CD, Terraform, Infrastructure as Code, observability platforms, planning tools, and developer portals.
• Enable teams to estimate and compare cost before deployment, establish cost guardrails, and evaluate financial impact during design and architecture decisions.
• Partner with engineering teams to design cost-efficient cloud, container, AI, and hybrid solutions without compromising reliability, security, or performance objectives.
• Integrate cloud cost and usage data, observability telemetry, CMDB records, product metadata, financial systems, and business outcome datasets.
• Define data models, allocation logic, governance controls, and enterprise data-quality practices required for trustworthy FinOps insights.
• Develop forecasts, scenarios, anomaly detection, dashboards, and recommendations that support product planning, capacity decisions, and financial accountability.
• Configure and manage FinOps and analytical platforms to provide scalable, automated, and role-based experiences.
• Lead advisory sessions and enablement with engineering, finance, product, and business stakeholders to align technical decisions with financial and business objectives.
• Create standards and governance that encourage accountability while preserving team autonomy and delivery speed.
• Product ownership or product management experience delivering technical, data, platform, FinOps, or technology financial management capabilities.

None flagged.