First American (India) is a GCC (Global Capability Center) of the First American Financial Corporation (NYSE: FAF) family of companies. FAI is a proud member of the FORTUNE 500 companies and has been amongst the Fortune 100 Best Companies to Work For® list for eight consecutive years. First American Financial Corporation provides comprehensive title insurance, closing/settlement, property data and technology solutions. First American (India) creates quality solutions for its customers by combining software, back office, and knowledge processing operations to fulfill First American's business requirements. Our priorities are our employees, customers, and shareholders \- in that order. First American (India) has been ranked amongst India's Best Companies To Work For™ 2023: Listed amongst the Top 100 by Great Place To Work® India, FAI is also certified Best Workplaces for Women and Workplace with Inclusive Practices. Software Services helps build First American's product suite that encompasses the best in class Title Insurance, Settlement and Mortgage solutions platforms. Leverages technology product stack across Microsoft platform predominantly to develop, enhance and maintain the best in class applications. The R \& D division delivers solutions for the title insurance industry leveraging the best of NLP, AI and ML.**Job Summary**
The Senior FinOps Analyst role is critical for optimizing cloud spending and driving financial accountability and cloud strategy across engineering and business units. This senior position requires a seasoned professional who can think strategically across multiple business units and cloud providers, with a focus on identifying and tracking high\-impact savings initiatives. The role has expanded to include ownership of SaaS spend governance, AI/ML token and consumption cost management, and enterprise\-wide cloud financial controls as the organization scales its use of cloud\-native and AI\-powered services.
*Responsibilities**
Cloud Monitoring \& Reporting: Own and maintain a standardized process, using data analytics and reporting tools, providing context on cloud spending to senior leadership and keeping internal teams informed about their cloud usage and costs.
Cloud Financial Management: Coordinate with finance, senior leadership, and directors to manage the cloud lifecycle and identify financial constraints for cloud strategy across all teams and cloud providers (AWS, Azure, GCP).
Cost Optimization: Proactively identify, prioritize, and drive execution on opportunities to reduce costs and increase the value of cloud investments.
EDP Agreements: Advise senior leadership on negotiating reseller agreements, track progress towards commitments, and ensure the organization’s cloud strategy is reflective of any obligations.
Private Rate Discounts: Engage with 3rd\-parties offering service\-specific discounts and coordinate with engineering teams to review and implement.
Contractor Management: Coordinate with engineering contractors and their project managers to enforce cost constraints and include FinOps best practices in the statement of work.
Cost Allocation \& Chargeback: Coordinate with Accounts Payable and FP\&A to ensure cloud costs are correctly allocated and book chargebacks from shared services and bulk discounts.
Cloud Strategy \& Governance: Establish a FinOps program to promote best practices, define policies and standards (e.g. chargeback, tagging, resource deployments), and enforce cost visibility and accountability.
Initiative Tracking \& Reporting: Define clear KPIs to monitor the realized financial results of completed cloud initiatives and the forecasted results of future initiatives.
*Qualifications**
Experience: 3\-7 years working in a dedicated FinOps role at a SaaS company, with demonstrated experience spanning cloud infrastructure costs, SaaS spend management, and consumption\-based AI/ML cost governance.
Financial Acumen: Deep understanding of cloud pricing models and cost management features of at least one major cloud provider (AWS, Azure, or GCP). Proven ability to perform complex financial modeling, variance analysis, and business case development for optimization initiatives.
Technical Acumen: Deep understanding of cloud infrastructure and services of at least one major cloud provider (AWS, Azure, or GCP) and experience rightsizing containerized and non\-containerized cloud workloads.
Cloud \& SaaS Spend Governance: Hands\-on experience building or maturing a SaaS spend management program, including license management, vendor contract governance, shadow IT controls, and chargeback frameworks. Familiarity with SaaS management platforms (e.g. Zylo, Torii, Flexera, Apptio) is strongly preferred.
AI \& Token Cost Management: Familiarity with token\-based and consumption\-based pricing for AI/ML services (e.g. OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI). Experience building cost observability for LLM APIs, implementing budget guardrails, and partnering with engineering teams to optimize prompt efficiency and model selection.
Communication \& Organization: Exceptional verbal and written communication skills with the ability to present complex subjects clearly and concisely. Capable of presenting financial and strategic insights to senior leadership followed by actionable insights to more technical audiences (developers and engineers).
*Expected Performance**
Data \& Reporting: Information is made available quickly, is accurate, and is actionable by stakeholders.
Total Annualized Cloud Savings: Define annual targets for cloud savings and track progress.
Forecasting Accuracy: Continuously improve the organization’s ability to accurately forecast expenses over 1\-year, 3\-year, and 5\-year timelines.
Cost Visibility \& Accountability: Implement FinOps governance policies to ensure cost accountability and adherence to best practice standards.
SaaS Spend Reduction: Establish baseline SaaS spend metrics and deliver measurable savings through license rightsizing, vendor consolidation, and renewal optimization.
AI/Token Cost Efficiency: Track cost\-per\-token and cost\-per\-inference trends across AI services; demonstrate quarter\-over\-quarter improvements in AI cost efficiency through optimization initiatives.
Optimizations: Collaborate with engineers to increase the value of the organization’s cloud investments through FinOps initiatives and coordinate with leaders to optimize cloud strategy towards business objectives.
Operations: Manage the organization’s pre\-ordered capacity and drive progress towards FinOps initiatives while maintaining cost accountability and visibility across cloud, SaaS, and AI consumption spend.
FAI is committed to create an environment that respects, supports and inspires all individuals. We do not discriminate on the basis of color, religion, sex, gender identity, sexual orientation and age. At FAI, we celebrate diversity and believe that an inclusive workforce benefits employees, the organization and our community. We are an Equal Opportunity Employer. For more information about our company and dedication to putting People First, check out https://firstam.wd1\.myworkdayjobs.com/faicareers.
Stakeholder Collaboration: Collaborate with directors and engineering teams to align optimizations with development initiatives to create a cloud strategy that delivers within financial constraints.
Capacity Optimization: Manage the purchase of pre\-ordered capacity for the organization (e.g. savings plans, reserved instances, pricing tiers) to balance savings with flexibility while avoiding waste.
Tooling \& Automation: Oversee and optimize the FinOps tool stack (e.g. Apptio Cloudability, native cloud tools, and custom data analytics) to drive speed, accuracy, and quality of FinOps data and automation.
SaaS Spend Governance: Build and maintain a comprehensive SaaS spend management program that provides full visibility into the organization’s software subscriptions, licenses, and vendor contracts.
SaaS Inventory \& License Management: Maintain an authoritative inventory of all SaaS subscriptions and licenses across business units, identify redundant or underutilized tools, and work with procurement to rationalize the portfolio.
Vendor \& Contract Optimization: Partner with procurement and legal to negotiate SaaS agreements, enforce renewal governance, and identify consolidation opportunities that reduce total cost of ownership.
SaaS Cost Allocation \& Chargeback: Establish chargeback/showback frameworks for SaaS costs by team, product, and cost center to drive accountability and align spend with business value.
SaaS Policy \& Controls: Define and enforce SaaS procurement policies including approval workflows, acceptable\-use standards, and shadow IT controls to prevent unauthorized spend.
Usage \& Adoption Analytics: Leverage SaaS management platforms (e.g. Zylo, Torii, Flexera, or Apptio) to track license utilization and adoption rates, flagging low\-usage seats for rightsizing or elimination.
AI Token \& Consumption Management: Own the financial governance of AI/ML inference costs, API consumption, and token\-based pricing across all AI services used within the organization.
Token Cost Visibility \& Reporting: Develop dashboards and reporting pipelines that track token consumption and associated costs by team, product, model, and use case for LLM and AI API services (e.g. OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI).
Consumption Budget \& Alerting: Define token and API consumption budgets per team and product line, implement automated alerting for threshold breaches, and enforce guardrails to prevent runaway spend.
Model \& Tier Optimization: Collaborate with AI/ML and engineering teams to evaluate trade\-offs between model capability and cost, recommending prompt optimization, caching strategies, model tiering, and batching to reduce per\-unit token costs.
Consumption\-Based Pricing Governance: Establish governance frameworks for consumption\-based and metered SaaS pricing models, ensuring contracts include appropriate usage caps, overage protections, and volume commitment structures.
AI FinOps Chargeback: Implement token\-level cost allocation and chargeback/showback mechanisms so that AI costs are attributed accurately to the products and teams driving consumption.
Committed Use \& Reserved Capacity: Analyze consumption patterns to identify opportunities for provisioned throughput, committed use discounts, or pre\-purchased capacity for AI services, balancing cost savings with throughput flexibility.
Education: Bachelor degree in Finance, Information Technology, or a related field. Master of Business Administration is a plus.
Certifications: FinOps Certified Practitioner, FinOps Certified Engineer, FinOps Certified FOCUS Analyst, and other cloud certifications are highly desirable. Certifications or coursework related to AI/ML cost management or SaaS Operations are a plus.