FinOps Analyst

Title:          Sr. FinOps AnalystLocation:   LATAM/remote (Central Time Hours)Duration:   Until 3/31/26Requirements: Must be able to prove residency with photo ID Key Skills: MUST BE FinOps Certified (any of the following: FinOps Certified Practitioner, FinOps Certified Professional, FinOps Certified Engineer), AWS  ScopeStandardize OpenAI budget management processes by integrating the OpenAI spend into existing cloud cost governance frameworks, including showback reporting and monthly team target forecasting. Partner with the Cloud Economics team to enhance proactive engagement with R&D teams, driving cost visibility, accountability, and operational efficiency across Indeed's AI/LLM investments. Key Responsibilities:In collaboration with the existing Cloud Economics Team, the new contractors will be responsible for the following key deliverables over the course of the next year:Standardized OpenAI Budget Management: The team will fully standardize the management of the new OpenAI budget. This involves aligning its operational processes with the reporting and optimization practices already established across the wider R&D organization. A key part of this is implementing the OpenAI budget into primary cost reporting tools such as Datadog and Stitcher to ensure full visibility. Enhanced Reporting and Alerting Automation: To improve efficiency and timeliness, current manual reporting processes will be integrated directly into our core cost indexes, data pipelines, and automated alerting systems. AI-Powered Cost Analysis and Explanation: The team will pioneer the use of AI and Large Language Models (LLMs) to provide clear, automated, and context-aware explanations for cloud cost drivers. By experimenting with LLM-based tools, the goal is to generate narratives that help individual engineering teams understand the specific factors influencing their spending. This will reduce the manual effort required by the Cloud Economics team to investigate and explain cost fluctuations, empowering teams to manage their own cloud usage more effectively. AI Usage Best Practices: The team will research and define clear guidelines for the effective use of AI services. This includes documenting both ""virtuous usage patterns"" to encourage and ""antipatterns"" to avoid, helping engineering teams innovate cost-effectively. These guidelines will inform the tracking systems. Target/budget tracking system: The engineering contractor will partner with the Observability and Cloud Econ teams to implement a proof-of-concept target tracking system for large spending team cloud targets, helping R&D teams with integrated tools and data to manage their team resource usage in a self-service manner.  Technical Skills. 5-7 Years of experience Public Cloud cost management tools (AWS Cost Explorer, Apptio, Kion, CloudHealth, or Cloudability, etc.) AWS preferredHands-on cloud experience (AWS preferred, GCP, or Snowflake)SQLDatabase and data warehousing conceptsMicrosoft Excel and/or Google Sheets (advanced proficiency)Data harvesting, transformation, and analysisFinOps fundamentals and executionMandatory Technical FinOps Certification Exposure to Machine Learning environments