Senior AI Deployment Manager, Cyber

We are a technology services company dedicated to helping organizations build and deploy cutting-edge AI solutions. From generative AI and custom LLM integrations to predictive analytics and intelligent automation, we work across industries to bring real-world AI applications to life. Our projects combine deep technical expertise with hands-on client collaboration to solve high-impact problems.

The Senior AI Deployment Manager leads complex AI product and delivery work in Eliza's Cyber vertical. You will serve as the product counterpart to client leaders and business development, translating cybersecurity needs into feasible AI opportunities and owning delivery alignment from discovery through launch. You will work closely with forward-deployed engineers, owning product decisions while engineering partners own implementation decisions in their lane.

This is a founding role in the Cyber vertical. You will operate independently through ambiguity, set direction for client work and teammates, and stay close enough to delivery to keep commitments and outcomes credible. Engagements may include cyber-domain discovery and, when the work calls for it, training on AI governance and Codex setup.

Eliza is AI-native and expects leaders to use AI tools in discovery, product definition, and client communication. The technology and client context evolve quickly; sound judgment means knowing where AI is useful, where it is not, and when to bring engineering or domain expertise into a decision.

• Run structured discovery with cyber stakeholders to understand workflows, risk, data readiness, and business outcomes.

• Assess use-case fit, feasibility, sequencing, and the path to production; make clear recommendations on what is ready for AI and what is not.

• Build and maintain a prioritized use-case backlog grounded in feasibility, readiness, and measurable impact.

• Translate client needs into product requirements, acceptance evidence, delivery plans, and product roadmaps engineers can act on.

• Partner with forward-deployed engineers through design, evaluation, iteration, launch, and handoff; surface edge cases and risks early.

• Manage the gap between prototype and production, including data quality, security, compliance, and scalability concerns.

• Align client executives, subject-matter experts, business development, and technical teams on scope, tradeoffs, timing, and measurable value.

• Define success criteria with client experts for AI systems whose performance requires ongoing evaluation.

• Communicate progress and risks plainly, challenge unsuitable requests constructively, and escalate decisions at the right time.

• Contribute AI governance and ChatGPT and Codex setup training when required by an engagement.

• Turn proven Cyber delivery methods into reusable playbooks, evaluations, and production-readiness practices.

• Coach Associates and help shape how enterprises move from AI experimentation to production in cyber contexts.

• Support pre-sales of cyber client engagements, including drafting and reviewing SOWs, work plans, and playbooks.

• Deep cybersecurity experience and sound judgment about the operating context behind client problems.

• A record of independently leading complex client or product work through ambiguity and measurable outcomes.

• Strong AI fluency: practical use of current AI tools and a clear understanding of where models help, fail, and require evaluation.

• Product judgment that connects user needs, business impact, feasibility, data readiness, risk, and technical constraints.

• Credible partnership with engineers; know which decisions belong to product and when to bring in engineering expertise.

• Clear executive communication, concise written materials, and confidence facilitating difficult tradeoff conversations.

• Experience setting direction for others or coaching less-experienced delivery teammates.

• AI governance, cyber risk, Codex setup, or responsible AI training experience.

• Consulting or client-service experience with executive stakeholders.

• Experience building reusable delivery methods, evaluations, or workflow assets.