Principal Technical Product Manager

Responsibilities

• 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.

Requirements

• 8+ years of product management for deeply technical products; engineering or CS background.
• Technical fluency: 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: 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.

Nice-to-Haves

• 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.