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Finance Operations (FinOps) Analytics Architect (Agentic AI Expertise) - Vice President
Singapore, Singapore · Job Posted May 03, 2026
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Job Description
The FinOps Analytics Architect is a senior technical leader responsible for driving cloud cost optimization, building cost-observability platforms, and enabling proactive cloud financial governance. In addition to core FinOps responsibilities, this role now incorporates Agentic AI architecture, governance, and cost-control capabilities as organizations shift from traditional dashboards to autonomous optimization systems.
Job Responsibility
Conduct deep architectural reviews of high-spend cloud services to identify inefficiencies
Recommend code-level and infrastructure changes to reduce spend
Ensure engineering teams adopt cost-efficient design standards
Build cloud cost observability and on-prem analytics frameworks
Develop forecasting models, dashboards, anomaly-detection systems, and financial models
Integrate data from cloud providers, usage logs, telemetry, and AI agent activity streams
Develop automated governance scripts and IaC controls for proactive enforcement
Implement tagging standards, cost attribution, chargeback/showback frameworks, and compliance policies
Design and integrate Agentic AI systems that autonomously analyze cloud usage, detect inefficiencies, and propose or execute optimizations
Establish per-agent cost attribution and build telemetry pipelines
Design dynamic budgeting models and implement policy-driven controls for agentic workflows
Govern agent estates using enterprise-grade tooling
Leverage or build Citi AI optimization agents
Manage cost implications of LLM inference, multi-agent collaboration, and RAG workflows
Partner with FinOps Champions and stakeholders to translate cost goals into actionable backlogs
Drive ongoing cloud and agent-driven optimization initiatives
Requirements
Expertise in cloud architecture (AWS, Azure, GCP) with hands-on cost optimization experience
Strong mastery of FinOps principles, cost models, and cloud financial governance
Experience with Python, SQL, Terraform/IaC, cloud billing datasets, and telemetry instrumentation
Understanding of LLMs, multi-agent architectures, RAG workflows, and AI operational cost models
Ability to design secure, monitored, and budget-controlled environments for autonomous agents
Nice to have
FinOps Certified Practitioner / FinOps Certified Professional
Experience with AI agent platforms such as Azure Copilot Optimization Agent or enterprise agent governance systems
Background in MLOps, AI Systems Architecture, or autonomous AI engineering