Sr. Managing Consultant - Technology Value Management

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, Red Hat, and leading IBM Consulting AI assets, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As Senior Managing Consultant in Technology Value Management, you make the cost and return of a client's technology visible and defensible to both the chief information officer and the chief financial officer. You bring that discipline into cloud and operating model engagements, so every placement and sourcing recommendation carries a fully burdened unit cost. Design technology cost transparency using the Technology Business Management taxonomy, mapping general ledger cost through to applications and services. Define the cloud cost allocation, showback and chargeback model that client finance and platform teams then run under the FinOps Foundation framework. Design the TBM and FinOps practice that keeps those models running: roles, decision rights, review cadence and a maturity path the client can follow after the engagement ends. Identify where cloud and software spend can be reduced, separating one-off savings from structural efficiency that holds across a budget cycle. Define unit cost metrics such as cost per transaction or per customer, and express cloud placement decisions in those terms. Bring AI model and inference cost into the same taxonomy, and test token yield: whether AI use cases remain economically viable at production volume. Build technology budgets and forecasts with client finance, and prioritize investment across run, grow and transform. Define how TBM and FinOps platforms are used across the engagement, separating what the platform delivers as standard from the taxonomy, allocation and governance work it can't do. Benchmark technology spend against defensible peer sets, without letting the benchmark become the target. Prepare software license positions ahead of renewal, timed to the negotiating window. Track benefits realization against the baseline set in the business case through to the financial statements. Build technology and AI business cases from a measured baseline of how the work runs today, the cost of controls and compliance, so the return a client is promised survives a risk review. Manage a team of consultants and work alongside cloud and operating model colleagues on joint engagements. This job can be performed from anywhere in the US. Extensive experience in technology finance or cloud cost advisory roles, including direct experience leading client workstreams. Hands-on experience designing Technology Business Management cost models or cloud allocation and chargeback models, and handing them over to client teams to run. A record of building technology investment business cases from a measured baseline that client finance accepted. Working knowledge of the FinOps Foundation framework and the Technology Business Management taxonomy. Hands-on experience with at least one TBM or FinOps platform, and the ability to separate what the platform delivers from the advisory work around it. Fluency with capital and operating treatment of cloud and software, and comfort working directly with finance functions. FinOps Certified Practitioner or Technology Business Management (TBM) Council certification. Experience with AI cost structures, including inference and token-based pricing. Experience with Apptio, Cloudability, Kubecost or Turbonomic. Software licensing experience with major enterprise vendors. Background in cloud strategy or modernization business cases. Familiarity with how AI governance and regulatory obligations change the cost of AI use cases.