Research Engineer (Azure Optimization)

Cloudzero

Boston, MA

Full Time

Mid Level

3 days ago

Job Description

About the Role

CloudZero is on a mission to help engineering teams build cost-efficient, scalable systems in the cloud. We're the industry's leading cloud cost intelligence platform, and we're expanding our efforts to bring advanced Azure optimization to the heart of our platform and services. We're looking for a Research Engineer with deep Azure expertise to help discover and develop cost-saving strategies, automation logic, and insights that directly shape our product and guide our customers toward better cloud economics.

Key Responsibilities

Investigate and analyze real-world Azure environments to surface inefficient configurations, underutilized resources, and design patterns with high cost-to-value ratios.
Develop and validate cost optimization strategies across Azure services like Virtual Machines, Storage, SQL, Functions, AKS, and more.
Prototype optimization logic and models in Python (or equivalent) and SQL, integrating with CloudZero's data pipeline.
Write scalable, reusable scripts for simulation, modeling, and recommendation generation.
Collaborate closely with Data Science, Engineering, and Product teams to convert research into customer-facing intelligence.
Stay on top of Azure pricing changes, savings plans, reserved instance models, and service evolution to inform internal logic and customer guidance.
Support the integration of ML-based techniques into optimization workflows (e.g., workload classification, anomaly detection).
Work with platform APIs and metadata to detect signals and patterns that drive actionable recommendations.

Requirements

Strong analytical skills and experience modeling savings strategies in Azure environments.
Strong knowledge of Azure services and pricing models — especially EC2, S3, RDS, Lambda, and autoscaling strategies.
Proficiency in one or more high-level programming languages such as Python, JavaScript, Java, C# etc. (for scripting, automation) and SQL (for data exploration and transformation).
Hands-on software development experience and experience using APIs and working with cloud infrastructure metadata.
Familiarity with DevOps, Infrastructure-as-Code, and CI/CD tools.
Comfort with documenting and communicating technical ideas clearly, especially when turning research into product features or internal tools.
A collaborative mindset — you'll be working across Product, Engineering, and Customer Success to land meaningful results.
Current, unrestricted authorization to work in the United States permanently.