Senior Cloud FinOps Engineer

About the job

We are seeking a highly technical Senior Cloud FinOps Engineer specialized in designing, developing, and deploying AI-powered agents and automation systems that proactively monitor, analyze, and optimize multi-cloud spend (AWS, Azure, GCP) in a large-scale research and academic healthcare environment. Responsibilities: • Research, design, and develop AI / ML-driven agents and automation workflows that continuously ingest cloud billing, usage, and tagging data (via APIs such as AWS Cost Explorer, Azure Cost Management + Billing, GCP Billing exports, CUR, etc.). • Build predictive models to forecast spend, identify upcoming eligibility for Savings Plans / Reservations, and recommend optimal purchase strategies (term length, payment option, instance family / region / zone / SKU, convertible vs standard) while factoring in performance SLAs and workload variability typical of research computing. • Implement real-time anomaly and spike detection with intelligent alerting (Slack, email, ServiceNow, etc.) that includes root-cause analysis and suggested corrective actions. • Develop automated tagging governance engines that detect missing / incorrect tags, suggest or auto-apply corrections (via Lambda / Functions / Azure Automation), and enforce research grant and department chargeback policies. • Create "recommendation-as-code" pipelines that generate executable Infrastructure-as-Code (Terraform / CloudFormation / Bicep) or direct API calls to purchase / commit to the optimal savings instruments. • Design and maintain a centralized FinOps AI dashboard (Power BI + custom web frontend if needed) that surfaces agent-generated insights, confidence scores, projected savings, and one-click approval workflows. • Integrate the AI platform with existing tooling (AWS Cost Anomaly Detection, Azure Advisor, third-party FinOps platforms) and extend them where native capabilities fall short. • Collaborate on containerized / microservice architecture (Kubernetes / EKS / AKS / GKE) for the agent platform and ensure all components meet healthcare security and compliance standards. • Continuously measure savings attribution, model accuracy, and automation adoption; iterate on models using retraining pipelines and feedback loops. • Document architectures, create runbooks, and mentor FinOps analysts and cloud engineers on using the new AI capabilities.

Requirements

• AI
• ML
• Cloud Engineering
• FinOps

Qualifications

• Bachelor’s or Master’s degree in Computer Science
• Data Science
• Engineering or a related quantitative field

Preferred Technologies

• AI
• ML
• Cloud Engineering
• FinOps

About the company

Zapcom Group Inc specializes in integrating technology and consulting services to optimize financial operations in cloud environments, with a focus on AI-powered solutions for various applications.