AI Deployment Manager

About Eliza

• 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.

Responsibilities

• You are not expected to specialize equally in both areas, though experience across both is welcome.
• In either path, you’ll work closely with clients, understand how their teams operate, use AI thoughtfully, and stay accountable for results.

Discover client needs and define the opportunity

• Lead stakeholder and user conversations to understand business goals, workflows, pain points, data readiness, and adoption barriers.
• Assess AI use-case fit, feasibility, risk, timing, and potential impact; make clear recommendations about what is ready to pursue.
• Align client stakeholders on priorities, target users, milestones, and measures of success.

Build: shape and deliver AI products and workflows

• Translate business needs into product requirements, specifications, acceptance criteria, product roadmaps, and delivery plans engineers can act on.
• Partner with engineers through design, evaluation, iteration, launch, and handoff; engineering owns implementation and infrastructure decisions.
• Surface edge cases, data quality, compliance, and scalability risks as work moves from prototype toward production.

Enablement: help client teams adopt AI

• Design and lead trainings, workshops, and office hours that help people apply AI in their daily work.
• Co-build, test, and refine prompts, skills, and workflows with client champions; make limitations and review needs clear.
• Turn effective practices into learning materials, curricula, and reusable templates.

Measure outcomes and improve the work

• Define success criteria with client experts, including for AI systems that need ongoing evaluation.
• Track product and adoption signals such as usage, realized business outcomes, and time saved; distinguish measured results from early indications.
• Use evaluation results, participant feedback, and adoption evidence to improve the solution and follow-up.

Align stakeholders and scale what works

• Manage scope, dependencies, risks, and client cadence while keeping business stakeholders, subject-matter experts, and technical teams aligned.
• Communicate progress, decisions, and tradeoffs clearly; raise feasibility concerns and challenge low-value requests early.
• Prepare and facilitate executive steering committee meetings that share progress and shape future opportunities with clients.
• Package proven delivery methods, learning materials, and workflow assets for reuse across engagements.
• Own meaningful AI work from client discovery through delivery or adoption.
• Work directly with client teams on practical AI use cases and workflows.
• Partner closely with engineers, client leaders, and subject-matter experts.
• Help shape reusable product delivery and enablement methods across engagements.

Requirements

• Eliza is AI-native: you will use AI tools across discovery, product definition, workflow building, training, and client communication, and explain where they help and where they fall short.
• Client work moves quickly and can change as users and evidence reveal new needs; we value thoughtful preparation, adaptability, and reliable follow-through.
• You should bring meaningful depth in at least one of the following areas.
• Experience across both is welcome but not required.
• Product or delivery experience translating business needs into requirements and coordinating with engineering to move AI or software solutions toward launch.
• Ability to assess feasibility, define acceptance evidence, and manage delivery tradeoffs as prototypes move toward production.
• Experience in client enablement, training, learning and development, adoption, customer success, or change work.
• Ability to facilitate practical learning and help users translate their workflows into AI-supported practices and clear adoption measures.
• Strong AI fluency: practical use of current AI tools and a clear understanding of model strengths, limitations, and safeguards.
• Sound judgment across client needs, business outcomes, technical constraints, and risk; know when to bring in engineering expertise.
• Human-centered design mindset: translate user needs into intuitive AI experiences, apply sound UX judgment, and use research and testing to refine solutions.
• Clear facilitation, executive communication, concise writing, organization, and reliable follow-through.

Preferred

• Experience across both Build and Enablement.
• MBA background.
• Hands-on experience developing prompts, skills, or workflows with enterprise client teams; or experience with adult learning, curriculum design, or adoption measurement.
• Exposure to enterprise software delivery, including backlogs, requirements, sprints, or evaluation work.
• Experience in finance, private equity operations, healthcare, or another domain Eliza serves.

Benefits

• Competitive compensation (base salary + performance incentives tied to client outcomes).
• Equity options in a growing AI services company.
• Exposure to a wide range of industries and high-impact AI problems.
• Travel opportunities for on-site client engagements (if desired).
• A collaborative, mission-driven team passionate about the real-world impact of AI.

Qualifications

• Required
• Build background
• Enablement background
• Shared strengths