Senior FinOps Analyst ID94366

AgileEngine•San Francisco, CA

About The Position

AgileEngine is seeking a Senior FinOps Analyst to advise R&D teams on cloud cost management and optimization. The role supports teams during 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 consultative resource for engineering teams, helping them understand spending, investigate cost variances, forecast upcoming costs, and identify actionable optimization opportunities. The role also contributes to AI/LLM cost monitoring, reporting, cost education, and technical documentation.

Requirements

At least 4 years of senior-level FinOps or cloud financial operations experience.
Authorization to work for any US employer; the company is unable to sponsor or take over employment visa sponsorship.
Proficiency in complex SQL or SQL-adjacent queries for analyzing cost and usage data and investigating variable cost anomalies.
Strong cloud cost management and optimization expertise.
Ability to investigate spend 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, with the ability to learn and use 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, responding to questions in real time through Slack and other asynchronous channels.
Meet proactively with key spending teams, especially APAC-based colleagues, to review monthly cloud spending, identify cost opportunities, and understand engineering roadmaps and upcoming spend.
Document engagement notes and recommendations, including recurring questions and emerging cost patterns.
Monitor cloud and AI/LLM spend for anomalies, cost spikes, and inefficiencies; investigate variances, write root-cause analyses, and recommend optimizations.
Document investigations and recommendations in Jira and flag relevant items for monthly reporting.
Participate in monthly forecasting by aligning central forecasts with team-level projections, surfacing discrepancies, and documenting teams' plans for upcoming spend.
Prepare monthly forecast engagement notes for assigned team cohorts.
Contribute FinOps insights 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 help requests through Slack, email, and other channels.