FinOps Observability PO
Remote
Long Term Contract.
TaxTerm: W2
Role overview
Own and prioritize FinOps initiatives to ensure visibility, governance, and optimization of cloud and AI spend across multi-cloud environments. Partner with stakeholders to translate cost optimization opportunities into actionable product features and delivery roadmaps.
Key responsibilities
Own and manage the FinOps product backlog including epics, features, and user stories aligned to cost optimization goals
Drive Cloudability implementation, enhancement, and adoption for cost visibility, showback/chargeback, and reporting
Leverage Datadog metrics/logs to identify inefficiencies, correlate performance with cost, and define optimization actions
Define and track FinOps KPIs such as cost trends, utilization, savings, forecast accuracy, and unit economics (including AI workloads)
Establish governance for AI consumption (LLMs, APIs, GPU workloads) including usage tracking, budgeting, and cost guardrails
Collaborate with engineering teams to drive optimization levers (rightsizing, scheduling, reserved capacity, model optimization, prompt efficiency)
Work closely with finance to align budgets, forecasts, and cost allocation models (showback/chargeback) across cloud and AI spend
Enable financial planning and analysis (FP&A) for cloud and AI consumption, including forecasting, variance analysis, and ROI tracking
Facilitate Agile ceremonies and ensure delivery of prioritized cost optimization initiatives
Build stakeholder alignment through regular reporting, dashboards, and executive updates
Enable governance practices including tagging standards, cost allocation, and policy adherence
Required experience
5-8+ years in FinOps / Cloud Financial Management / Product Ownership roles
Hands-on experience with Cloudability (Apptio) for cost reporting, dashboards, and governance
Experience using Datadog for observability, monitoring, and performance-cost correlation
Strong understanding of cloud cost optimization strategies (rightsizing, RI/SP planning, tagging, automation)
Experience managing AI/ML or GenAI cost consumption (e.g., model usage, API billing, GPU/compute cost optimization)
Experience working with finance teams on budgeting, forecasting, and cost governance
Experience working in Agile/Scrum environments and managing product backlogs
Ability to translate technical cost drivers into business and financial outcomes
Good to have
Experience with AWS, Azure, or Google Cloud Platform cost models and native tools
Exposure to AI cost monitoring tools or frameworks (e.g., model usage tracking, token-based billing)
Experience with Power BI or dashboards for executive reporting
FinOps certification (Practitioner or equivalent)
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