AI FinOps & Technology Finance Analyst in Chennai, भारत

Key Responsibilities : 1. AI FinOps and Cost Optimization : - Monitor and analyze AI-related expenditure across cloud AI services, generative AI platforms, large language models (LLMs), APIs, GPU/CPU compute, storage, and model hosting.- Track costs associated with AI model training, fine-tuning, inference, token consumption, embeddings, vector databases, and AI-powered applications.- Develop cost allocation and chargeback/showback models for AI and cloud consumption across business units, projects, and product teams.- Identify opportunities to optimize AI workloads through model selection, prompt optimization, token reduction, caching, batching, and efficient resource utilization.- Establish unit economics metrics such as cost per inference, cost per 1,000 tokens, cost per AI transaction, and cost per customer or business outcome.- Partner with technical teams to evaluate cost-performance trade-offs across different AI models, cloud services, and deployment architectures.2. Cloud and Technology Financial Management : - Monitor and optimize cloud expenditure across platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP).- Analyze spending on compute, storage, networking, databases, SaaS applications, software licenses, infrastructure, and third-party technology services.- Track technology consumption against budgets, forecasts, and approved business cases.- Identify cost-saving opportunities through rightsizing, resource scheduling, reserved capacity, savings plans, license optimization, and elimination of unused resources.- Support technology contract reviews, vendor spend analysis, renewal planning, and procurement negotiations.- Evaluate the financial impact of technology architecture changes, cloud migrations, and AI adoption initiatives.3. Budgeting, Forecasting, and Financial Planning : - Support annual budgeting, quarterly forecasting, and periodic financial reviews for AI, cloud, and technology portfolios.- Analyze actual expenditure against budget, identify variances, and provide explanations and corrective recommendations.- Develop cost models and financial forecasts based on usage trends, business growth, AI adoption, and technology roadmaps.- Prepare financial business cases for AI initiatives, cloud transformation programs, technology investments, and automation projects.- Assess ROI, total cost of ownership (TCO), payback periods, and expected financial benefits of AI and technology investments.- Support financial planning and analysis (FP&A) activities, accruals, purchase order tracking, and technology expense reporting.4. FinOps Governance and Reporting : - Develop dashboards and management reports covering AI, cloud, and technology spending, utilization, cost trends, and optimization opportunities.- Establish cost allocation policies, tagging standards, budgets, alerts, and financial accountability frameworks.- Track savings initiatives, cost avoidance, realized savings, and optimization benefits.- Define KPIs and performance metrics for AI and cloud financial management.- Support FinOps governance reviews and communicate cost insights to finance leaders, engineering teams, and business stakeholders.- Maintain documentation of cost optimization initiatives, assumptions, forecasts, and financial controls.5. AI Investment Analysis and Business Value : - Assess the financial viability of AI use cases, including generative AI, intelligent automation, predictive analytics, and enterprise AI solutions.- Compare build-versus-buy options and evaluate proprietary models against commercial APIs and open-source alternatives.- Analyze AI project costs across development, deployment, integration, monitoring, maintenance, and ongoing inference.- Measure realized business benefits, including productivity improvements, operational savings, revenue impact, and process efficiencies.- Partner with product and business teams to establish business cases and track benefits realization.- Support responsible AI investment decisions by incorporating scalability, reliability, security, compliance, and operating costs into financial assessments.6. Stakeholder and Vendor Management : - Collaborate with Finance, IT, Engineering, Data Science, AI/ML, Procurement, and business teams to improve cost visibility and spending discipline.- Work with cloud providers, AI vendors, SaaS providers, and technology partners to review usage, pricing, billing, and contractual commitments.- Present actionable financial insights and recommendations to senior management.- Drive awareness of cost-efficient technology usage and promote a culture of financial https://jobeax.com/link/iurSvqgG50T6eIR5 Qualifications : - Bachelor's degree in Finance, Accounting, Economics, Business Administration, Information Technology, or a related field.- Typically 2 - 5 years of experience in financial analysis, FP&A, cloud cost management, technology finance, FinOps, or a related role.- Understanding of cloud billing models, technology cost structures, software licensing, and subscription-based services.- Working knowledge of AI/ML services, generative AI platforms, LLM APIs, and the cost drivers associated with AI workloads.- Experience with budgeting, forecasting, variance analysis, cost allocation, and financial reporting.- Strong Excel skills and experience building dashboards or reports using Power BI, Tableau, or similar tools.- Ability to analyze large datasets, identify spending patterns, and translate findings into actionable business recommendations.- Strong communication, stakeholder management, problem-solving, and analytical https://jobeax.com/link/Cexs453KRiH2S1rJ Qualifications : - FinOps Certified Practitioner or equivalent FinOps training.- Certifications in AWS, Microsoft Azure, Google Cloud, or cloud financial management.- Experience with cloud cost management tools such as CloudHealth, Apptio Cloudability, Flexera, AWS Cost Explorer, Azure Cost Management, or Google Cloud Billing reports.- Familiarity with financial planning tools such as Anaplan, SAP, Oracle, Workday Adaptive Planning, or similar platforms.- Basic SQL and experience with data visualization or analytics tools.- Understanding of AI cost monitoring, model usage analytics, token pricing, GPU utilization, and LLM observability tools.- Exposure to technology procurement, vendor negotiations, and cloud commitments. (ref:hirist.tech)