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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. 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
Implement tagging standards, cost attribution, chargeback/showback frameworks, and compliance policies
Manage FinOps governance foundations
Design and integrate Agentic AI workflows into FinOps
Establish per-agent cost attribution and traceability
Build telemetry pipelines with cost metadata
Design dynamic and iterative budgeting models for agentic workflows
Implement policy-driven controls for autonomous agents
Govern agent estates using enterprise-grade tooling
Leverage or build Citi AI optimization agents
Oversee safe implementation of agent-suggested optimizations
Manage cost implications of LLM, multi-agent, and RAG architectures
Optimize model selection, context length, inference endpoints, and caching strategies
Partner with FinOps Champions, engineering teams, and business stakeholders
Promote organizational alignment
Communicate cost insights to executives and product teams
Drive ongoing cloud and agent-driven optimization initiatives
Develop long-term cloud, AI, and automation strategy
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