Associate AI Deployment Manager

Eliza • Remote, US,

1d

About The Position

The Associate AI Deployment Manager executes scoped work within client AI engagements, helping turn discovery into useful product delivery or client adoption. Candidates may bring depth in Build, organizing product definition and delivery with engineering teams, or Enablement, helping client teams learn and apply AI through training, workshops, and workflow development. Experience in both areas is welcome but not required, and the role offers opportunities to learn across the full AI Deployment craft.

The Associate works with an AI Deployment Manager or another workstream owner who sets direction and priorities. They own assigned tasks and delivery artifacts, keep progress visible, and raise questions and blockers early. Eliza is AI-native, so the role uses AI tools across discovery, requirements, workshop preparation, workflow building, and client communication, while explaining where those tools help and where they fall short. Client work moves quickly and may change as new information emerges; sound judgment, clear communication, and reliable follow-through are valued.

The role is part of a technology services company delivering generative AI, custom LLM integrations, predictive analytics, and intelligent automation across industries, combining technical expertise with hands-on client collaboration.

Requirements

• Meaningful experience in at least one of the following areas: Build or Enablement; experience across both is welcome but not required.
• Build background: Experience in product, consulting, technical program management, customer success, or a related setting, with examples of turning conversations into requirements, plans, or delivery artifacts.
• Build background: Strong organization and follow-through across tasks, backlogs, dependencies, testing, or client workstreams.
• Enablement background: Experience in client-facing delivery, training, facilitation, learning and development, adoption, or a related setting.
• Enablement background: Ability to prepare clear learning materials, explain AI in practical terms, and help users apply new tools in their workflows.
• Strong AI fluency, including practical use of current AI tools and a working understanding of their capabilities, limitations, and safeguards.
• Clear written and verbal communication; able to work with business stakeholders and technical teams without jargon or overselling.
• Human-centered design mindset: translate user needs into intuitive AI experiences, apply sound UX judgment, and use research and testing to refine solutions.
• Sound organization, reliable follow-through, comfort with changing needs, and a habit of asking sharp questions and escalating early.

Nice To Haves

• Experience across both Build and Enablement.
• Hands-on experience with prompts, skills, or lightweight automations, or experience designing training content or facilitating workshops.
• Exposure to enterprise software delivery, including requirements, backlogs, sprints, QA, or evaluation work.

Responsibilities

• Participate in stakeholder and user discovery; document workflows, needs, constraints, and desired outcomes.
• Translate conversations and research into requirements, user stories, workshop plans, decision logs, product roadmaps, and next steps for the workstream owner.
• Maintain use-case and action trackers so priorities, dependencies, and open questions remain visible.
• Maintain backlogs, requirements, roadmaps, and delivery artifacts as client needs and priorities change.
• Coordinate practical dependencies with client partners, designers, and engineers, including data, access, calendars, and decisions.
• Run test sets or evaluation steps when needed; log failure modes and summarize evidence for review.
• Prepare and help facilitate trainings, persona-specific workshops, and office hours for client teams.
• Build and refine exercises, prompts, skills, and workflows with client champions; document their use, known limitations, and review needs.
• Gather participant feedback and update learning materials and follow-up actions based on user needs.
• Track delivery progress and adoption signals, such as usage, realized business outcomes, and time savings, distinguishing measured results from early indications.
• Prepare concise client readouts on progress, decisions, risks, and next steps.
• Keep notes, action items, workshop materials, and assigned engagement artifacts current.
• Coordinate with client stakeholders and Eliza delivery partners to keep assigned work on track.
• Raise blockers, feasibility concerns, and risks early so the workstream owner can respond.
• Use feedback and evidence to improve the work and contribute reusable delivery or learning assets.
• Deliver inside client engagements and contribute to practical AI products, workflows, adoption, reusable playbooks, workshop materials, and delivery assets.

Benefits

• Competitive compensation consisting of base salary and 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.
• Hands-on experience delivering inside real client engagements and building the full AI Deployment craft.
• Work with client teams on practical AI products, workflows, and adoption.
• Partnership with AI Deployment Managers, engineers, client champions, and leaders.
• Opportunity to contribute to reusable playbooks, workshop materials, and delivery assets.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed