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Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.
The 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 Responsibilities
1. Cloud Architecture Optimization & Technical Advisory
Conduct 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 Transparency
Build 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 Controls
Implement tagging standards, cost attribution, chargeback/showback frameworks, and compliance policies.
Manage FinOps governance foundations promoting visibility, accountability, and cross‑team alignment.
4. Agentic AI Responsibilities
Agentic 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 FinOps
Architect 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 & Ownership
Establish 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 Control
Design 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 Automation
Leverage 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 Architectures
Manage 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 consumption.
5. Cross-Functional Collaboration & Stakeholder Leadership
Partner with FinOps Champions, engineering teams, and business stakeholders to translate cloud and AI cost goals into actionable backlogs.
Promote organizational alignment via shared ownership of cloud and and on-prem AI spending across finance, engineering, and operations.
Communicate complex On-prem, cloud, and AI cost insights clearly to executives and product teams.
6. Continuous Cloud & AI Optimization Strategy
Drive ongoing cloud and agent-driven optimization initiatives to reduce waste, prevent cost overruns, and maximize ROI.
Develop long-term cloud, AI, and automation strategy including SKU optimization, licensing, GPU provisioning, and model lifecycle cost management.
Required Qualifications
Exposure to cloud architecture (AWS, Azure, GCP) with hands‑on cost optimization experience.
Good knowledge of FinOps principles, cost models, and cloud financial governance.
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.
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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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View Citi’s EEO Policy Statement and the Know Your Rights poster.
Eligibility typically includes the qualifications and experience outlined in the job description above, with around 0-5 Years years of relevant experience expected for this role.
The key responsibilities for this role are detailed in the Key Responsibilities section above, covering the core duties expected of a Finops Analytics - Assistant Vice President at Citi Bank.
This role requires around 0-5 Years years of relevant experience, as specified in the job listing. Please refer to the Qualifications & Experience section above for full details.
Skills relevant to this position are outlined in the Qualifications & Experience section above. In general, strong communication, domain knowledge, and the ability to meet role-specific targets are valued across similar BFSI positions.
You can apply directly using the Apply Now button on this page, which will take you to Citi Bank's application process for this role.