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.
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
What you'll do:
Own product definition, roadmap, and metrics across the office of the CTO's agentic AI portfolio: an enterprise knowledge assistant (Brain), an agent-driven engineering platform (Springboard), and enterprise AI/data modernization and app development.
Translate CTO strategy into crisp requirements, milestones, exit criteria, and KPIs — then hold the line on them.
Drive adoption of internal platforms: reduce onboarding friction, instrument usage, track NPS and active users, and run developer advocacy and objection handling.
Shape product direction for foundation-model based autonomy architectures and model lifecycle tooling (evaluation, fine-tuning, verification, deployment).
Run continuous discovery with engineers, operators, and executive stakeholders; turn findings into prioritized backlogs.
Prioritize ruthlessly across competing initiatives with small teams and aggressive timelines.
Analyze the agentic tooling, enterprise AI platform, and foundation model ecosystem; recommend build/buy/partner positions to leadership.
Author strategy documents, product briefs, and executive updates that drive decisions.
Manage transitions of maturing products from incubation to owning organizations.
Required qualifications:
8+ years of product management for deeply technical products; engineering or CS background.
Technical fluency: you read code, work APIs and CLIs from a terminal, and prototype with AI coding tools yourself.
Shipped developer tools, internal platforms, or AI/ML products — and drove their adoption.
Working fluency in LLM-based systems: agents, evaluation, context management, fine-tuning trade-offs.
Metrics-driven operating style: you define KPIs, instrument products, and report against thresholds and objectives.
Exceptional written communication — requirements, strategy docs, executive briefs.
Proven stakeholder management up to the executive level across engineering, product, and business functions.
Fluid intelligence that allows one to operate effectively in ambiguous conditions while finding opportunities to drive technical efforts and force multiply.
This role requires travel to a Shield AI location 1-3 times per quarter
Preferred qualifications:
Prior experience as a software engineer.
Experience in defense, aerospace, or other regulated environments (CUI/ITAR, restricted or disconnected deployments).
Experience with enterprise data platforms (e.g. Databricks) and ERP/business-system integration.
Experience with safety-critical or assurance-driven software processes (requirements traceability, V&V, certification artifacts).
Experience taking zero-to-one internal products through incubation, adoption, and handoff.
Experience with robotics or autonomy products.