Hybrid Infrastructure FinOps Engineer II will be responsible for tracking and optimizing AI cloud infrastructure costs while ensuring maximum performance and efficiency. FinOps engineer will work closely with our finance, operations, and CloudOps teams to analyze AI and non-AI cloud usage patterns, identify cost-saving opportunities, and implement strategies to manage and optimize cloud expenditure. 

• Automate the creation of reports and dashboards to visualize cloud cost trends for AI production and non-production usage 

• Develop and maintain cost allocation models. 

• Stay up-to-date on cloud pricing models and best practices. 

• Analyze cloud usage patterns for cost optimization. 

• Proficiency in cloud platforms, Google Cloud Platform, and AWS. Some exposure to Azure is required as well 

• Building out tooling and automation to share cloud spending data across the organization for all AI and non-AI usage 

• Collaborating with cross-functional teams to align cloud spending with business objectives. 

• Developing and maintaining cost optimization policies and procedures. 

• Monitor and report on cloud expenditure.  

• Master’s degree in computer science and engineering is preferred.  

• 2+ years’ experience in automation and development with Infrastructure-as-Code tools such as Terraform, CloudFormation across different cloud platforms, or similar experience 

• 2+ years of experience of programming with tools such as Python, Ruby, Go, Git, Github, or Azure DevOps 

• 2+ years of experience in estimation, project management, and finops for cloud environments. 

• 2+ years of experience in cloud operations, financial management, or related roles. 

• Experience with cloud cost optimization frameworks such as FinOps. 

• FinOps Certified Practitioner / CAPM / other PM certifications. 

KNOWLEDGE/SKILLS/ABILITIES 

Required: 

• Collate, analyze and prioritize cloud optimization recommendations and calculate potential savings. 

• Experience in cloud cost optimization strategies. 

• Experience with cloud cost management tools. 

• Experience programming languages such as Python, Go, Ruby, etc. 

• Experience with financial concepts and budgeting. 

• Strong analytical and problem-solving skills. 

• Excellent communication and collaboration skills. 

• Automate cost optimization processes.