Senior FinOps Analyst ID94366

AgileEngine•San Francisco, CA

8d•Hybrid

About The Position

We are looking for a Senior FinOps Analyst to advise engineering teams on cloud costs and optimization. This role requires a schedule that covers APAC business hours (evening/night shift in LATAM/US), including a necessary overlap with PST and afternoon CST.

Requirements

Must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time.
4+ years of experience in FinOps.
Strong cloud cost management and optimization expertise.
Proven ability to investigate spend anomalies and produce written root-cause analyses.
Experience serving as a partner-facing resource, advising and consulting directly with R&D/engineering teams.
Cloud cost forecasting experience, including aligning central forecasts with team-level projections.
Familiarity with OpenAI/LLM cost drivers and monitoring LLM spend.
Cost modeling and team investment/project tracking.
Proficiency with Jira for documenting investigations and Slack for real-time, asynchronous support.
Experience in maintaining technical documentation/wiki spaces and contributing to recurring reporting, such as Showback.
Strong written and verbal communication for stakeholder engagement and reporting.
Availability to cover APAC business hours with necessary PST and afternoon CST overlap.
Upper-intermediate English level.

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, triaging and answering inbound questions in real time via the team's Slack channel and other asynchronous channels.
Conduct proactive, consultative engagement with key spending teams, especially APAC-based colleagues — to review monthly cloud spending, surface actionable cost opportunities, and understand upcoming engineering roadmap delivery plans before they become budget surprises; capture meeting notes and summaries with recommendations on top recurring questions and emerging cost patterns.
Proactively monitor cloud and AI/LLM spend for anomalies, cost spikes, and inefficiency patterns; conduct structured investigations into flagged variances, produce written root-cause analyses, and deliver actionable optimization recommendations to team owners, documenting the work on Jira tickets and flagging items for the monthly reporting.
Participate in the monthly forecasting cycle, engaging directly with assigned R&D teams to align central forecasts with team-level projections, surface discrepancies, and document team plans and intent for upcoming spend; produce monthly forecast engagement notes per assigned team cohort.
Contribute a FinOps practitioner perspective and team-sourced information, including AI/LLM cost drivers, to showback reporting and top spending R&D team meetings, maintaining an understanding of cost drivers.
Support Cost Awareness and Cost Education efforts, and audit and update the relevant space on the wiki.
Model team cost projections and respond to customer help requests via Slack, email, and other channels.