Strategic Growth Partners provides both operations and strategic support to commercial organizations. Our client is a leading global professional services firm dedicated to helping organizations tackle their most complex business issues, maximize stakeholder value, and deliver sustainable change.

Their Corporate Performance Improvement practice is looking for a FinOps and Technology Business Management (TBM) leader who bridges finance, engineering, and operations to align on-premises, cloud, and enterprise IT investments in a single combined. This is both a strategic role - defining combined on-premises and cloud financial management and TBM roadmaps - and a hands-on tactical role designing and implementing cost avoidance and cost reduction measures.

Workplace Type: 80% travel. Hybrid.

Employment Type: Full-Time.

Clearance: Active Top Secret Clearance; SCI eligibility preferred where required by the engagement.

Compensation: Hourly rate is DOE.

Experience Should Include

• Combined on-premises and cloud cost modeling, optimization, and benchmarking (government and/or commercial comparables) including AI workloads, and cost analysis of task orders.

• FinOps and TBM framework implementation - governance, tagging taxonomy, chargeback/show-back models and KPI frameworks.

• FinOps Open Cost and Usage Specification (FOCUS).

• Technology Business Management (TBM) - TBM Taxonomy cost pools, towers, and solutions; mapping on-premises data center, network, labor, and licensing costs together with cloud spend into one unified cost model.

• Workload rightsizing, auto-scaling, and commitment-based discount strategy (reserved instances, savings plans, committed-use agreements), including in classified or restricted cloud regions

• Orphaned/unused resource identification (cloud and on-premises) and remediation - VM rightsizing, guardrails, tagging automation.

• Native cloud cost management tools (AWS Cost Explorer, Azure Cost Management, GCP Billing, Oracle Cloud cost tools) and third-party FinOps and TBM platforms (Apptio, Flexera, CloudHealth) approved for government use.

• Government cost recovery and rate setting - working capital fund rate development, full-cost recovery principles, per-service and per-user cost baselines, and separating consumption-driven charges from fixed overhead.

• Enterprise software licensing consolidation and optimization, including duplicate licensing across organizations and classification levels.

• AI-assisted cost anomaly detection, forecasting, and optimization recommendation engines - must demonstrate active use of AI tools in delivery, within tools approved for the environment; AI fluency is required for this role.

• Federal Contracting, including working knowledge of FAR and DFARS requirements and task order ordering procedures.

Responsibilities

• Develop and execute comprehensive FinOps and TBM strategies aligned with mission goals and DWCF cost-recovery requirements, detailing frameworks, processes, and governance.

• Create and maintain FinOps roadmaps embedding cost-conscious practices into engineering and architecture lifecycles.

• Design KPI frameworks with clear targets and accountability mechanisms to monitor FinOps delivery.

• Establish governance frameworks for tagging, budgeting, and resource accountability - including guardrails to prevent unnecessary resource allocation.

• Drive automation and transparency in cost reporting, anomaly detection, and forecasting - providing real-time visibility into combined on-premises and cloud spend across mission partners.

• Build per-service and per-user cost baselines and pricing transparency that customers can use to compare current costs with rates and plan budgets, including advance cost estimates for emerging services.

• Build ROI models and cost reduction business cases that quantify optimization impact for executive audiences.

• Integrate findings into A&M's broader engagement scope and deliverables.

• Build a unified TBM-based cost model that maps on-premises and cloud costs to IT towers, services, and mission partners, enabling like-for-like comparison and workload placement decisions.