Business Value Manager

Overview

This individual contributor role focuses on translating complex data and AI capabilities into quantified business outcomes. The Business Value Manager partners with account teams and customer executives to shape investment decisions, influence deal structures, and support enterprises transitioning toward AI-native operating models.

Responsibilities

• Serve as the business value architect for strategic deals within a defined sales territory.
• Take ownership of value-focused customer engagements, including direct stakeholder mapping and alignment with senior sales leaders and supporting account teams.
• Embed quantified, forward-looking value narratives into deal strategy, linking AI platform architectures and emerging AI operating models to revenue uplift, cost optimization, and risk reduction.
• Engage C-suite stakeholders to shape enterprise AI and data strategies and position the organization within shifts toward platform consolidation, hybrid architectures, and AI-enabled business models.
• Build and present CFO-grade business cases, including TCO, ROI, NPV, and IRR, and incorporate evolving cost dynamics such as inference workloads, utilization patterns, and long-term AI operating economics.
• Lead value discovery engagements that map current-state environments to future-state AI-native architectures, quantifying value drivers, investment trade-offs, and execution pathways.
• Support complex, multi-year deal cycles with commercial structuring, scenario modeling, and competitive positioning against cloud-native and AI platform alternatives.
• Align solution design with commercial objectives by partnering with Sales, Solutions Engineering, and Product to optimize architectures for performance, scalability, and durable economic efficiency in AI-driven environments.
• Contribute to global value selling thought leadership and enablement efforts, including value management-specific initiatives and cross-functional initiatives.
• Develop value frameworks and value calculation methodologies; build value case studies and realization studies in partnership with customers.
• Develop and launch value-based corporate sales plays.
• Represent the organization in executive forums, articulating perspectives on enterprise AI economics, architectural trade-offs, and long-term implications of AI adoption on cost structures and operating models.
• Use AI tools and automation (including LLMs and agentic workflows) to scale analysis, accelerate insight generation, and industrialize repeatable assets such as TCO models and scenario simulators.

Requirements

• 5+ years in value engineering, strategy consulting, or equivalent customer-facing roles.
• Experience driving customer engagements and/or working cross-functionally with a large or dynamic organization.
• Strong structured reasoning skills and deep experience with quantitative analysis.
• Excellent communication skills; ability to distill complex technical and financial concepts into clear, actionable insights.
• Hands-on deal and sales experience, including working closely with Sales teams in complex, high-value enterprise deals.
• Strong commercial and financial acumen, including advanced financial modeling (DCF, NPV, IRR) and ability to connect technology decisions to P&L, balance sheet, and cash flow outcomes.
• Demonstrated ability to influence enterprise deal cycles, including shaping deal strategy, positioning, and commercial outcomes.
• Solid understanding of modern data platforms, distributed systems, and AI/ML workloads (including data pipelines, model deployment, and infrastructure trade-offs).
• Ability to quantitatively reason about evolving cost drivers in AI and data environments, including compute, storage, and workload patterns.
• Hands-on experience using AI tools (e.g., LLMs and automation frameworks) to support analysis, modeling, and content generation.
• Strong executive presence; ability to engage and influence CIO, CFO, CDO, and senior business stakeholders.
• High ownership mindset and ability to operate independently in ambiguous, high-growth environments.

Preferred Qualifications

• Experience or knowledge of data and AI software and infrastructure, including modern AI stack (runtime, MLOps, inference, SLM/LLM model types) and key Apache projects (Spark, Trino, Kafka, etc.); experience with modern AI stack and private/hybrid/public cloud data and AI deployments; familiarity with DevOps.
• Experience designing or deploying enterprise AI or data platform architectures in production environments.
• Deep expertise in one or more industries: Financial Services, Manufacturing, Consumer Goods, or Telecommunication.
• Experience building scalable value engineering assets such as TCO calculators, benchmarking models, or scenario simulators.
• Familiarity with hybrid and on-prem AI deployments, including cost and performance trade-offs versus public cloud.

Compensation & Benefits

• This role is not eligible for immigration sponsorship.
• Anticipated annual base salary range by location:
  • California: $125K–160K
  • Colorado: $115K–140K
  • Illinois: $115K–140K
  • Washington: $125K–160K
• Individual compensation within the published range is determined by the candidate’s skills, experience, qualifications, and primary work location.
• In addition to base pay, sales roles may be eligible for a commission plan, while non-sales roles may be eligible for a corporate incentive plan.
• Comprehensive benefits package.

Location

United States (role salary range varies by primary work location as listed above).