FinOps Engineer

We are looking for an experienced Cloud Financial Engineer to join our engineering organization and drive infrastructure cost optimization, spend visibility, and resource efficiency. In this role, you will act as a deeply technical partner—bridging the gap between cloud architecture and financial accountability. Rather than just compiling reports, you will actively write code, develop automation tools, analyze usage telemetry, and lead cloud optimization initiatives end-to-end alongside DevOps and engineering leads.

Core Responsibilities

• Tooling & Automation Engineering: Write code and build custom internal tooling to gain granular spend visibility, track usage patterns, and improve infrastructure efficiency.

• Architecture & Kubernetes Optimization: Apply deep technical knowledge of cloud primitives and container orchestration (Kubernetes) to uncover waste and streamline resource allocation.

• Commitment Portfolio Management: Strategically oversee cloud commitment plans (Savings Plans, Reserved Instances, Committed Use Discounts) to optimize bottom-line spend.

• Anomaly Detection & Telemetry: Design and maintain automated systems to track cost spikes, trigger alerts, and provide real-time health tracking for cloud spend.

• Showback / Chargeback Frameworks: Implement cloud cost allocation models to map infrastructure consumption accurately back to specific engineering squads and products.

• FinOps Culture Champion: Drive a culture of financial awareness across R&D teams, partnering with technical leads to translate efficiency insights into direct engineering actions.

What You’ll Bring

• Hands-on Cloud Experience: Practical experience managing cloud environments (GCP proficiency is a strong advantage).

• Engineering & Scripting: Software development capabilities to build custom internal automation, coupled with advanced SQL skills for data manipulation.

• Infrastructure Depth: Strong conceptual and practical understanding of modern cloud infrastructure, containerization, and Kubernetes.

• Cloud Economics: Thorough mastery of cloud billing mechanisms, pricing tiers, Spot instances, and commitment models.

• AI Tooling Integration: Practical experience utilizing modern AI tools and LLM workflows to boost engineering productivity.

• Ownership & Communication: Proactive mindset with strong analytical skills and the ability to articulate technical recommendations to both business and engineering stakeholders.

• Security Clearance: Active Security Clearance (or eligibility to obtain one) – Mandatory.