Finops Analytics - Assistant Vice President

Single PositionExplore a Career With UsView All JobsFinops Analytics - Assistant Vice PresidentCHENNAI, Tamil Nādu, India +1 moreNo longer accepting applications.Job ID26978380Date posted07/09/2026DepartmentTechnologyThe FinOps Analytics is a under 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.Agentic AI introduces autonomous AI agents capable of analyzing data, making decisions, and executing actions at scale—requiring new guardrails, real‑time cost management, and AI-centric FinOps frameworks.Key Responsibilities1. Cloud Architecture Optimization & Technical AdvisoryConduct reviews of high‑spend cloud services to identify inefficiencies.Recommend code‑level and infrastructure changes—including serverless patterns, right‑sizing, and storage tiering—to reduce spend.Ensure engineering teams adopt cost‑efficient design standards to prevent cloud and on-prem “tech debt.”2. FinOps Data, Analytics & Cost TransparencyBuild cloud cost observability and on-prem analytics frameworks that provide real‑time usage and spend insights.Develop forecasting models, dashboards, anomaly‑detection systems, and financial models to support cloud budgeting.Integrate data from cloud providers, usage logs, telemetry, and AI agent activity streams.3. Governance, Policy Automation & Cloud Financial ControlsImplement tagging standards, cost attribution, chargeback/showback frameworks, and compliance policies.Manage FinOps governance foundations promoting visibility, accountability, and cross‑team alignment.4. Agentic AI ResponsibilitiesAgentic AI introduces autonomous, reasoning‑capable AI agents that perform tasks, invoke APIs, spin up compute, and make resource decisions independently—requiring a new layer of FinOps oversight.Design & Integrate Agentic AI Workflows into FinOpsArchitect and integrate Agentic AI systems that autonomously analyze cloud usage, detect inefficiencies, and propose or execute optimizations.Incorporate multi‑agent systems capable of proactive anomaly detection, predictive optimization, and autonomous corrective actions within the cloud and on-prem ecosystem.Real‑Time AI Agent Cost Visibility & OwnershipEstablish per‑agent cost attribution, including owner tags, budget identifiers, and full traceability of every model invocation or API call.Build telemetry pipelines (e.g., OpenTelemetry with cost metadata) capturing cost_per_call, decision logs, and tool usage for all agents.Budgeting, Guardrails & Autonomous Spending ControlDesign dynamic and iterative budgeting models, replacing static annual budgets with daily/weekly limit enforcement for agentic workflows.Implement policy-driven controls (e.g., budget throttles, automated revocation, execution guardrails) to manage microtransaction-level spend driven by autonomous agents.Govern agent estates using enterprise-grade tooling (e.g., Microsoft’s Foundry Control Plane) to enforce identity, security, and auditability for AI agent actions.AI Optimization Agents & Execution AutomationLeverage or build Citi AI optimization agents (e.g., Azure Copilot Optimization Agent) that automatically analyze performance, compare SKU alternatives, and generate execution-ready automation scripts.Oversee the safe implementation of agent-suggested optimizations by validating performance impact and compliance before execution.FinOps for LLM, Multi-Agent & RAG ArchitecturesManage the cost implications of LLM inference, multi-agent collaboration, and retrieval-augmented generation (RAG) workflows, where token usage and replication can multiply costs significantly.Optimize model selection, context length, inference endpoints, and caching strategies to reduce unnecessary LLM...