Director of Business Value from Enterprise AI
Jobgether · United States · Yesterday
RemoteRemoteEngineering$280k–$420k/yrFull-time
Accountabilities
- Own and lead the end-to-end demand-to-value pipeline for enterprise AI initiatives, including opportunity identification, prioritization, solution evaluation, adoption, and ROI measurement.
- Partner with business leaders and executives to identify high-value use cases and transform ambiguous challenges into actionable AI opportunities.
- Evaluate and prioritize AI initiatives based on business impact, technical feasibility, risk, cost, and organizational readiness.
- Lead buy-versus-build assessments, including vendor evaluations, market analysis, recommendation development, and implementation oversight.
- Establish baselines, KPIs, and success metrics to measure business outcomes and demonstrate tangible value from AI investments.
- Drive enterprise adoption strategies through training, communication plans, change management initiatives, and stakeholder engagement programs.
- Serve as a strategic advisor to non-technical leaders, translating complex AI concepts into business-focused recommendations and actionable insights.
- Build, lead, and mentor a high-performing team responsible for business engagement, demand shaping, and enterprise AI execution.
- Develop strategic roadmaps, governance processes, and operational frameworks that enable scalable AI adoption across multiple business functions.
- Collaborate with technical teams to validate vendor claims, assess model capabilities and limitations, and ensure solutions align with organizational objectives.
Requirements
- 15+ years of experience in business transformation, strategy, enterprise technology, operations, product leadership, or related executive roles.
- 5+ years of experience leading large-scale cross-functional programs, organizational transformations, or technology-driven initiatives with direct people management responsibilities.
- Strong technical understanding of modern AI, machine learning, and generative AI concepts, including model capabilities, limitations, training methodologies, evaluation frameworks, and practical deployment considerations.
- Demonstrated ability to differentiate traditional machine learning approaches from generative AI solutions and apply this understanding to strategic decision-making.
- Proven track record of translating business challenges into technology solutions that deliver measurable operational or financial outcomes.
- Experience leading vendor evaluations, procurement initiatives, and buy-versus-build decision processes.
- Expertise in defining business cases, ROI frameworks, performance metrics, and adoption measurement strategies.
- Strong executive communication and stakeholder management skills, with the ability to influence senior leaders and align diverse teams.
- Experience building and leading high-performing teams while creating scalable operating models and governance structures.
- Strong analytical thinking, strategic planning, and problem-solving capabilities in complex and evolving environments.
- Experience in enterprise AI, digital transformation, automation programs, consulting, or business-side product leadership is highly desirable.
- Familiarity with organizational change management methodologies and enterprise enablement strategies is preferred.
Benefits
- Competitive compensation package with a base salary range of $280,000 - $420,000 annually, depending on experience and location.
- Performance-based bonus opportunities.
- Equity participation as part of the total rewards package.
- Comprehensive healthcare and employee benefits programs.
- Fully remote work environment with flexibility across the United States.
- Opportunity to work on transformative AI initiatives with enterprise-wide impact.
- Exposure to cutting-edge AI technologies and strategic decision-making at the executive level.
- Career growth opportunities within a fast-moving, innovation-driven organization.
- Inclusive and collaborative culture that values leadership, innovation, and continuous learning.