#Sgunited Jobs AI Finops Engineer

Job Summary You will lead the management of Azure AI and GenAI consumption frameworks, enforce governance for cost attribution, and drive FinOps best practices to optimize AI innovation with financial efficiency and business value. Responsibilities Enforce governance standards and tagging practices to ensure accurate project-level cost attribution Maintain a centralized framework to provide full visibility into Azure AI and GenAI consumption across projects, teams, and applications Integrate Azure Cost Management, billing APIs, and monitoring systems to track consumption and costs Collaborate with ML/LLMOps teams to ensure cost observability in training, deployment workflows, and token usage Build dashboards and alerts to monitor real-time and forecasted costs, including anomaly detection for budget risks Deliver executive and project-level reporting linking cost to usage and business outcomes in partnership with the value tracking team Identify and recommend cost optimization opportunities and facilitate their implementation Champion adoption of FinOps best practices for AI workloads within the business unit Communicate technical cost drivers clearly in business-oriented language to stakeholders Apply problem-solving and innovation skills to balance AI workload performance with cost efficiency Maintain strong understanding of data policies and cost management in cloud environments Required competencies and certifications Bachelor’s degree in Computer Science, Engineering, or a related field Preferred competencies and qualifications 1-3 years of experience in cloud administration and/or operations Knowledge of Azure services, especially Microsoft Cost Management, Azure Monitor, and Databricks on Azure Proficiency with data engineering tools such as Python, SQL, and PySpark to process billing and usage telemetry Experience integrating with dashboards and BI tools like Power BI and Grafana Working knowledge of Infrastructure as Code (IaC) tools such as Terraform, Bicep, and ARM templates to enforce tagging and cost guardrails Hands-on experience in cloud FinOps, including budgeting, forecasting, cost allocation, and anomaly detection Strong communication skills to explain technical cost drivers in business terms Problem-solving and innovation mindset to optimize AI workloads balancing cost and performance Strong grasp of data policies and cost management in cloud environments