Description

Key Responsibilities

 • Process and analyze large volumes of AI cost and usage data across teams and platforms. • Track actual spend against forecast, surface variances early, and report detailed actuals. • Design, build, and maintain leadership dashboards for AI model cost visibility. • Identify and support cost-optimization opportunities with data-backed recommendations. • Standardize metrics and definitions so cost reporting is consistent and trusted. • Partner with engineering and finance stakeholders to refine reporting requirements. Tech Stack • Amazon Quick Suite for BI and dashboarding • SQL for large-scale data analysis • Dev360/program dashboard frameworks • Data visualization and executive reporting Required Skills & Experience • 5–10 years of relevant professional experience in data analysis, BI, or analytics engineering. • Proven, verifiable results delivering analytics and dashboard solutions that drove real business decisions — with concrete examples of measurable impact. • Hands-on experience with Amazon Quick Suite or comparable BI tooling. • Strong SQL skills and comfort working with large, messy datasets. • Experience building and maintaining program or executive dashboards. • Strong attention to detail and ability to explain variances crisply. • Experience building and/or leveraging AI agents (e.g., agentic workflows, LLM-based automation, AI-assisted engineering tools) to improve productivity and outcomes.

 Preferred Qualifications 

• Prior domain experience in cloud FinOps. • Familiarity with AI/LLM cost models (tokens, inference, training).

 What We Look For • Strong sense of ownership — takes end-to-end responsibility for outcomes, not just tasks. • Self-motivated and proactive; able to operate independently with minimal supervision. • A good team player who collaborates effectively across teams, geographies, and time zones. • Proven track record of delivering measurable results in previous roles

Key Skills

Education

Any Gradute