Sr Finance Manager- AI & Finance Transformation

This role sits at the intersection of Finance, Data, and AI. The mandate is to replace manual FP&A processes with scalable, intelligent systems, enabling the Technology FP&A (Network and IT) team to plan, forecast, and analyze spend more efficiently and accurately. Key Responsibilities Own AI‑driven transformation of FP&A workflows Identify high‑value use cases across Network and IT finance Replace legacy Excel/manual models with scalable, automated solutions Design and deploy agentic AI solutions Build or orchestrate agent‑based systems leveraging modern AI platforms (Anthropic, Google, OpenAI, etc.) Implement workflows that integrate reasoning, retrieval, and execution across financial datasets Integrate enterprise data ecosystems Connect and normalize data across Snowflake, Azure, and other platforms Incorporate structured and unstructured data from procurement, accounting, network systems, and IT Enable and scale adoption Train and guide finance teams on how to use AI tools and agent‑based workflows Establish best practices for prompt design, agent configuration, and model governance Drive governance and compliance Ensure solutions align with enterprise data, security, and financial controls Partner with Technology, Security, and Data teams on storage, retrieval, and access patterns Partner on future‑state systems Interface with ERP/EPM transformation efforts (SAP → Oracle) Ensure AI solutions integrate into long‑term finance systems architecture Education and Work Experience 7+ years in FP&A, Finance Transformation, Data, or related field Demonstrated experience building or deploying AI/ML or automation solutions (not just using them) Working knowledge of agentic AI concepts (multi‑step workflows, tool use, retrieval, orchestration) Strong understanding of FP&A fundamentals (forecasting, budgeting, variance analysis) Experience working with enterprise data platforms (Snowflake, Azure, etc.) Ability to translate ambiguous business problems into scalable technical solutions Hands‑on experience with AI platforms (Anthropic, Google, OpenAI, etc.) Experience integrating multiple enterprise data sources into unified models Exposure to ERP/EPM systems (SAP, Oracle) Background in Technology Finance (Network, IT, or similar) Experience enabling or training non‑technical users on advanced tools Required Qualifications Bachelor’s degree in Finance, Accounting, Economics, Computer Science, Data Science, Information Systems, Engineering, or related field At least 18 years of age Legally authorized to work in the United States Preferred Qualifications Master’s degree in Business Administration (MBA), Data Science, Analytics, Computer Science, Information Systems, or related discipline Compensation Base Pay Range: $94,300 - $170,200 Corporate Bonus Target: 20% Travel and Regulatory Travel Required (Yes/No): No DOT Regulated Position (Yes/No): No Safety Sensitive Position (Yes/No): No Equal Opportunity Employer Statement T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated. Talent comes in all forms at the Un‑carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing View email address on click.appcast.io or calling View phone number on click.appcast.io. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non‑accommodation related requests. #J-18808-Ljbffr T-Mobile