FinOps AI/ML Engineering Lead | Multi-Cloud Cost Governance

Accenture PLC; Austin (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

Accenture's Cloud Advisory practice is a market leader in helping global enterprises achieve measurable financial and operational value from cloud investments. This role leads multi-cloud agentic AI automation initiatives, defines reference architectures, and guides squads to deliver production-grade automations with strong FinOps governance.

You will mentor managers and analysts, establish cost-control frameworks, and report KPIs with dashboards for executives.

Qualifications

• Minimum of 8 years in cloud engineering, AI automation, or platform architecture.
• Minimum of 3 years leading FinOps automation programs.
• Minimum 1 year experience in agentic AI frameworks and MCP integration.
• Bachelor’s degree in Computer Science, Engineering, IT, Data or equivalent work experience.

Responsibilities

• Define reference architectures for agentic AI orchestration across multi-cloud environments.
• Establish cost governance frameworks, budgets, tagging, and anomaly detection with IaC guardrails.
• Lead squads to implement agentic workflows, IaC modules, and policy libraries with CI/CD integration.
• Mentor associate managers, consultants, and analysts on automation best practices.
• Operationalize Responsible AI standards, including RBAC and secrets management.
• Define KPIs for automation coverage and realized savings; publish dashboards for executives.
• Support client proposals, workshops, and SOW development for agentic FinOps programs.

Skills

Cloud engineering

AI automation

Platform architecture

Education

Bachelor’s degree in Computer Science/Engineering/IT/Data or equivalent

Tools

OPA/Rego

Sentinel

Terraform

Bicep

ARM

GitHub Actions

Azure DevOps

Job description

Accenture's Cloud Advisory practice is a market leader in helping global enterprises achieve measurable financial and operational value from cloud investments. This role leads multi-cloud agentic AI automation initiatives, defines reference architectures, and guides squads to deliver production-grade automations with strong FinOps governance.

You will mentor managers and analysts, establish cost-control frameworks, and report KPIs with dashboards for executives.