## About the Role

This is a full-time, onsite position in the Denver Metro Area. Candidates must be available for at least one in-person interview, which may include a whiteboarding exercise or technical assessment.

The role sits between engineering planning and cloud spending, with responsibility for bringing cost estimation into project intake and approval workflows. It supports new initiatives by turning technical design inputs into financial models, helping teams understand the cost and value implications of architectural decisions early in the process.

A major part of the work is focused on AI initiatives. The position partners with architects, engineers, and senior leaders to compare projected and actual performance, strengthen forecasting accuracy, and create a repeatable framework for value capture across the delivery lifecycle.

## Key Responsibilities

– Integrate cloud cost estimation into engineering intake and project approval processes.
– Work with architects and engineering teams to convert technical inputs such as IOPS, data transfer, and compute into financial forecasts.
– Build and maintain reporting that compares projected costs with actual spend for new initiatives.
– Define, track, and present financial and operational metrics for senior leadership, including ROI analysis for deployed AI initiatives.
– Develop and scale a value-capture framework across the AI delivery lifecycle.
– Create templates, guidance, and role definitions to support intake and feasibility reviews.
– Advise on project selection and identify cloud cost-avoidance opportunities before resources are committed.
– Use Excel, SQL, and BI tools to analyze billing data and support valuation models.

## Required Skills

– Bachelor’s degree in Finance, Economics, or a related field.
– At least 5 years of experience in finance, corporate development, or valuation-focused roles.
– Advanced Excel-based financial modeling, business case development, and valuation skills.
– Ability to work with large datasets using SQL and BI tools.
– Professional experience with AI/ML technologies, including LLMs, prompt engineering, and the cost drivers of compute and data pipelines.
– Hands-on experience building AI chatbots, using low-code/no-code platforms, or developing internal tools through APIs.
– Strong project management skills with a collaborative and organized approach.
– Ability to translate complex financial concepts into practical engineering guidance.
– Strong strategic thinking and process design capabilities.
– Ability to train and educate business leaders on technology valuation, cloud consumption, and architecture trade-offs.
– A player-coach mindset.

## Preferred Skills

– AWS Certified AI Practitioner, Google Cloud Professional ML Engineer, or Microsoft Azure AI Fundamentals.
– MBA, CFA, or an equivalent advanced credential.
– Experience in a fast-paced technology environment or the telecommunications industry.

## Cloud Platforms & Technologies

### Cloud Providers
– AWS
– Azure
– Google Cloud Platform (GCP)

### Cloud Billing / Architecture
– AWS, Azure, or GCP billing platforms
– Cloud architecture
– Serverless architecture
– Graviton-based architectures

### Data & Analytics
– Excel
– SQL
– BI tools
– Billing datasets
– Metadata

### AI / ML
– AI/ML technologies
– LLMs
– Prompt engineering
– AI chatbots

### Development & Automation
– Low-code/no-code platforms
– APIs

## FinOps Responsibilities

– Build cloud cost estimates for new initiatives during intake and approval.
– Translate technical requirements into predictive spend models.
– Compare forecasted and actual cloud costs.
– Improve the accuracy of intake and forecasting processes.
– Track and report ROI and value delivered by AI initiatives.
– Establish a value-capture framework across the AI lifecycle.
– Identify cloud cost-avoidance options during project vetting.
– Support architectural decisions with cost and financial impact analysis.

## Compensation

– $83,950 to $119,900 per year

## Benefits

– Flexible spending accounts
– Health savings account (HSA)
– 401(k) plan with company match
– Employee stock purchase plan (ESPP)
– Flexible time away plan

## Why You Might Be Interested

This role offers the chance to work where finance, cloud economics, and AI delivery intersect. It has direct influence on project intake, forecast accuracy, and executive reporting, with visibility into how technical choices affect cost and return on investment. The work also includes building repeatable processes and helping stakeholders use them consistently. For someone with valuation experience and technical fluency, it provides a highly cross-functional seat in cloud and AI financial decision-making.