Senior FinOps Analyst: Remote Cloud Cost & AI Spend

AgileEngine, LLC.; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine, LLC in New York, NY is seeking a Senior FinOps Analyst to guide cloud spend for R&D teams and optimize costs, with a schedule aligned to APAC hours and overlapping PST/CST.

You will triage spend anomalies, perform root-cause analyses, forecast costs, and partner with engineering to drive cost-aware decisions across OpenAI/LLM usage while maintaining documentation and reporting.

Qualifications

• 4+ years of FinOps experience.
• Strong cloud cost management and optimization expertise.
• Ability to investigate spend anomalies and write root-cause analyses.
• Experience advising R&D/engineering teams and partnering with them.
• Cloud cost forecasting experience with team alignment.
• Familiarity with OpenAI/LLM cost drivers.
• Strong written and verbal communication.
• Availability to cover APAC business hours with PST/CST overlap.

Responsibilities

• Serve as primary FinOps contact for R&D teams via Slack and other channels.
• Lead monthly cloud spend reviews with APAC teams and advise cost opportunities.
• Investigate spend anomalies, document root cause analyses, and propose optimizations in Jira.
• Assist in monthly forecasting with R&D teams and align forecasts.
• Contribute to showback reporting and cost-driver awareness.
• Maintain wiki documentation and recurring reports.

Skills

FinOps

Cloud cost management

Root-cause analysis

Stakeholder engagement

Forecasting

OpenAI/LLM costs

Cost modeling

Jira

Slack

Documentation/wiki

Tools

Jira

Slack

Job description

AgileEngine, LLC in New York, NY is seeking a Senior FinOps Analyst to guide cloud spend for R&D teams and optimize costs, with a schedule aligned to APAC hours and overlapping PST/CST.

You will triage spend anomalies, perform root-cause analyses, forecast costs, and partner with engineering to drive cost-aware decisions across OpenAI/LLM usage while maintaining documentation and reporting.