S
Shield AIvia Lever
Director of Business Value from Enterprise AI (R5463)
REMOTEPosted 2d ago
OtherExecutiveFull-time#ai-lab
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About the Role
Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description:
This Director owns the full demand-to-value pipeline: sensing where the business needs help, separating signal from noise, identifying the highest-leverage opportunities, deciding when to buy versus build, driving adoption, and proving measurable ROI.
This role is the AI team's primary operator with non-engineering functions across Shield, and is expected to build and lead the team that executes this pipeline at scale. Success is defined by turning scattered interest into a focused portfolio of business-backed use cases, converting pilots into real adoption, and demonstrating hard value in ways that earn trust, budget, and follow-on demand.
While this role is business-facing rather than a technical builder, it requires genuine technical grounding in machine learning and generative AI. Sound buy/build calls, credible use-case shaping, and defensible ROI cases all depend on the leader understanding what these systems can and can't do, how they're evaluated, and where the real technical risk sits — not just what vendors claim.
Job Description:
This Director owns the full demand-to-value pipeline: sensing where the business needs help, separating signal from noise, identifying the highest-leverage opportunities, deciding when to buy versus build, driving adoption, and proving measurable ROI.
This role is the AI team's primary operator with non-engineering functions across Shield, and is expected to build and lead the team that executes this pipeline at scale. Success is defined by turning scattered interest into a focused portfolio of business-backed use cases, converting pilots into real adoption, and demonstrating hard value in ways that earn trust, budget, and follow-on demand.
While this role is business-facing rather than a technical builder, it requires genuine technical grounding in machine learning and generative AI. Sound buy/build calls, credible use-case shaping, and defensible ROI cases all depend on the leader understanding what these systems can and can't do, how they're evaluated, and where the real technical risk sits — not just what vendors claim.
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