FinOps Engineer III

Love's Travel Stops & Country Stores•Oklahoma City, OK

4d•Onsite

About The Position

The FinOps Engineer is responsible for advancing Love’s Cloud Financial Management program through a blend of technical engineering, financial analytics, and intelligent automation. This role leverages AI-driven insights, automation, and data visualization to optimize cloud and infrastructure spend across AWS, Azure, GCP, VMware, and Data Center environments. As a key contributor to Infrastructure Services, the FinOps Engineer ensures that every technology dollar supports measurable business value. They build and maintain automated systems that collect, analyze, and visualize cost data, using artificial intelligence and advanced analytics to improve forecasting accuracy, detect anomalies, and enhance decision-making. This position will be located in-office at Love's Corporate HQ in Oklahoma City.

Requirements

4–7 years of experience in cloud engineering, FinOps, or infrastructure financial management.
Deep understanding of cloud billing and pricing models (AWS, Azure, GCP).
Experience with scripting and automation (Python, PowerShell, Terraform, or similar).
Working knowledge of AI and machine learning tools for data analysis or forecasting (e.g., Python ML libraries, Azure ML, AWS Forecast, or AI-powered BI tools).
Proficiency in data visualization platforms such as Power BI, Tableau, or Snowflake.
Familiarity with FinOps Framework principles and cost governance best practices.
Bachelor’s degree in Computer Science, Information Systems, Finance, or related discipline.

Nice To Haves

FinOps Certified Practitioner (FCP) certification preferred.

Responsibilities

AI-Enabled Cost Optimization & Automation
Develop automation and AI-assisted scripts (Python, PowerShell, or Terraform) to identify unused resources, forecast consumption trends, and recommend optimization opportunities.
Integrate cost and usage data into enterprise analytics platforms (e.g., Snowflake, Power BI) using AI or machine learning models to enhance accuracy and trend detection.
Implement intelligent tagging compliance and anomaly detection to identify deviations in spend patterns automatically.
Partner with engineering and SRE teams to embed AI-driven insights into CI/CD pipelines and infrastructure lifecycle management.
Financial Analysis & Intelligent Reporting
Design and maintain dashboards and visualizations that present complex cost data through AI-powered insights, predictive models, and automated summaries.
Use AI tools to summarize and present cost insights in leadership-friendly formats, highlighting key trends, risks, and opportunities.
Collaborate with Finance to develop AI-assisted forecasting and budget variance models for multi-cloud environments.
Contribute to ongoing improvement of the enterprise FinOps scorecard and monthly executive reports through automation and natural language summaries.
Governance & Collaboration
Define and maintain cloud tagging and cost allocation policies, leveraging AI for compliance monitoring and data quality improvements.
Partner cross-functionally with Finance, Procurement, and Cloud Operations to align spend optimization with strategic goals.
Support modernization initiatives by applying AI-assisted analytics to evaluate total cost of ownership and ROI scenarios.
Participate in the FinOps maturity roadmap, integrating automation and AI capabilities to drive continuous improvement.