The posting, in Shield AI's own words
archived Oct 23, 2026Shield 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, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. 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 role is a partner to the Director of Workplace AI. It focuses on collaborating with stakeholders to understand their business problems, shaping AI use cases, quantifying impact, and producing decision-quality analyses and materials that help the Director and VP make smart, fast calls. The person in this role will work across business units to clarify needs, analyze processes and data, support build-versus-buy recommendations, and track how AI solutions perform against baselines and ROI expectations.
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What you’ll do:
Work with business stakeholders to unpack ambiguous asks into clear problem statements, hypotheses about where AI adds leverage, and testable success criteria. Map current workflows, identify pain points and inefficiencies, and quantify potential impact of new AI solutions(e.g., time saved, error reduction, risk reduction, throughput gains). Collaborate with the Director and technical partners to define use-case scope, requirements, and business value; build simple business cases comparing options. Run targeted market research, compile vendor information, and build comparison frameworks (capabilities, cost, risk, fit) that inform the Director’s buy vs build recommendations. Partner with business teams to establish pre-deployment baselines; design practical, business-facing metrics and dashboards to track adoption and value post-deployment. Draft concise business case documents, evaluation summaries, and ROI updates that senior leaders can consume quickly and act on. Monitor usage and outcome data, compare performance against baselines and expectations, and highlight where AI solutions are succeeding or underperforming. Use data (feedback, usage, outcomes) to inform training focus, messaging, and iteration priorities; surface insights that help the Director fine-tune adoption strategies.