Senior FinOps Analyst ID94366

AgileEngine•Texas City, TX

About The Position

AgileEngine is seeking a Senior FinOps Analyst to advise R&D teams on cloud cost management and optimization. The role supports APAC business hours, which may mean evening or night shifts in LATAM or the US, with some overlap with Pacific Time and afternoon Central Time. The analyst serves as a key contact for cloud-cost guidance, supports forecasting and showback reporting, investigates spending anomalies, and helps teams understand and optimize cloud and AI/LLM costs.

Requirements

Authorized to work for any employer in the US; the company cannot sponsor or take over employment visa sponsorship.
At least 4 years of senior-level FinOps experience.
Proficiency in complex SQL or SQL-adjacent queries for analyzing cost and usage data and investigating variable-cost anomalies.
Strong expertise in cloud cost management and optimization.
Ability to investigate spending anomalies and produce written root-cause analyses.
Experience advising and consulting directly with R&D or engineering teams as a partner-facing resource.
Cloud-cost forecasting experience, including aligning central forecasts with team-level projections.
Familiarity with OpenAI/LLM cost drivers and monitoring LLM spend.
Experience with cost modeling and team investment or project tracking.
Experience maintaining technical documentation and wiki spaces and contributing to recurring reporting such as showback.
Proficiency with Jira for documenting investigations and Slack for real-time and asynchronous support.
Proficiency with FinOps and cloud-cost tools, and ability to learn new tools quickly.
Upper-intermediate English proficiency.

Nice To Haves

AI/LLM governance expertise.
AI/LLM variable cost management expertise.

Responsibilities

Serve as the primary point of contact for R&D teams seeking cloud-cost guidance, answering questions in real time through Slack and other asynchronous channels.
Engage proactively with spending teams, especially APAC-based colleagues, to review monthly cloud spending, identify cost-saving opportunities, and understand upcoming engineering plans.
Capture meeting notes and summaries, including recommendations, recurring questions, and emerging cost patterns.
Monitor cloud and AI/LLM spending for anomalies, cost spikes, and inefficiencies; investigate variances, write root-cause analyses, and provide actionable recommendations.
Document investigations in Jira and flag relevant items for monthly reporting.
Participate in monthly forecasting by aligning central forecasts with team projections, identifying discrepancies, and documenting plans and expected spending.
Produce monthly forecast engagement notes for assigned team cohorts.
Contribute FinOps expertise and team-sourced information, including AI/LLM cost drivers, to showback reporting and meetings with top-spending R&D teams.
Support Cost Awareness and Cost Education efforts and audit and update the cloud economics wiki space.
Model team cost projections and respond to customer help requests through Slack, email, and other channels.