Sr. FinOps Cloud Engineer

Overview

Senior FinOps Engineer serving as the technical backbone and subject matter expert for cloud financial operations across the global engineering organization, bridging cloud infrastructure, data engineering, and business economics.

What you'll do

• Manage, curate, and normalize end-to-end cloud cost and usage datasets across multi-cloud environments, ensuring high data fidelity, consistency, and standardized governance.
• Define, build, and maintain automated cost, usage, and efficiency dashboards using Apache Superset, supported by SQL and data extraction pipelines.
• Design and deploy automated anomaly detection algorithms, statistical models, and alerting mechanisms to detect spending spikes, runaway workloads, and unexpected cost regressions in near real time.
• Benchmark, track, and report on cloud consumption, forecast variance, unit economics, and realized savings to engineering teams and leadership.
• Implement and refine tagging governance, business cost-allocation models, and unit economics metrics such as cost per customer, cost per query, or cost per pipeline run.
• Own and optimize cloud financial management platforms for reporting, cost optimization, and performance measurement, including Cloudability, PointFive, ProsperOps, and Larridin; experience with comparable platforms is welcome.
• Design, build, and maintain automation workflows and scripts to identify and reclaim idle, underutilized, or orphaned resources, including compute instances, unattached volumes and IPs, outdated snapshots, and development/test environments.
• Lead enterprise-wide commitment strategies across AWS, Azure, and GCP, managing portfolio coverage, risk, and utilization for Reserved Instances, Savings Plans, and applicable provider-specific commitments.
• Partner with software, platform, and SRE teams to analyze utilization telemetry, implement rightsizing recommendations, and optimize compute and storage resources.
• Introduce and establish FinOps frameworks tailored to AI, ML training pipelines, and LLM inference workloads.
• Establish Total Cost of Ownership (TCO) and Return on Investment (ROI) models for AI infrastructure, including GPU clusters, vector databases, model hosting endpoints, and third-party AI APIs.
• Collaborate with AI/ML engineering teams to evaluate model inference performance against operational costs, improving token efficiency and hardware utilization.
• Establish and enforce cloud cost and operational policies across accounts, subscriptions, regions, and resource configurations.
• Participate in architectural design and cloud capacity planning for new projects, services, and major infrastructure changes.
• Oversee third-party cloud marketplace software procurement, ensuring spending aligns with enterprise budgets and cloud discount commitments.
• Review production release schedules from a cost-impact perspective, incorporating pre-production load-testing analysis and cost guardrails.
• Partner with Financial Planning & Analysis (FP&A) and engineering leaders to track monthly variance, improve forecasting models, and translate technical decisions into business impact.
• Collaborate with engineering, platform, and finance teams across India and the United States.
• Lead knowledge-sharing sessions, develop technical documentation, and promote FinOps best practices across engineering teams.

What you'll need

• 5+ years of hands-on experience in cloud engineering, DevOps, SRE, or cloud financial management.
• Strong expertise in AWS and/or Google Cloud, with familiarity with Azure.
• Proven experience applying FinOps principles (Inform, Optimize, Operate) in a modern cloud-native enterprise environment.
• Advanced SQL skills and experience building automated data workflows, metrics engines, and dashboards using BI tools such as Apache Superset.
• Experience creating or configuring automated alerting rules, statistical anomaly detection, or threshold-based algorithms for infrastructure telemetry.
• Direct experience managing cloud commitment portfolios, including Savings Plans and Reserved Instances, and optimizing effective savings rates.
• Strong scripting or coding skills in Python, Bash, or Go to build automated resource reclamation, API integrations, and policy enforcement tools.
• Strong communication skills and demonstrated ability to contribute to architectural planning, implement governance policies, and explain trade-offs between cost, performance, reliability, and delivery speed.

Nice to have

• FinOps Certified Practitioner or FinOps Certified Professional certification.
• Cloud Architect or SysOps certifications (AWS, Azure, or GCP).
• Experience implementing FinOps practices for AI/ML workloads and GPU compute environments, including TCO/ROI analysis for LLMs and distributed training.
• Experience with cloud marketplace procurement workflows and private offer agreements.
• Experience with container cost allocation across Kubernetes, EKS, GKE, or AKS using tools such as Kubecost or OpenCost.
• Working knowledge of the FinOps Open Cost and Usage Specification (FOCUS), including its schema and taxonomy standards.

Details

• Location: Bangalore, India.
• Collaboration across India and the United States.
• Access to software/technology subject to U.S. export controls; any job offer is contingent on the applicant's capacity to serve in compliance with U.S. export controls.