FinOps Observability PO

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)