About Us

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.

Job Summary

The Associate AI Deployment Manager executes scoped work inside client AI engagements, helping turn discovery into useful product delivery or client adoption. We’re interested in candidates with depth in either of two areas: Build, helping organize product definition and delivery with engineering teams; or Enablement, helping client teams learn and apply AI through training, workshops, and workflow development.

You’ll work with an AI Deployment Manager or other workstream owner who sets direction and priorities. You’ll own assigned tasks and delivery artifacts, keep progress visible, and raise questions and blockers early. You are not expected to arrive with expertise in both Build and Enablement; you’ll have opportunities to learn across the full AI Deployment craft.

Eliza is AI-native: you will use AI tools across discovery, requirements, workshop preparation, workflow building, and client communication, and explain where they help and where they fall short. Client work moves quickly and can change as new information emerges; we value sound judgment, clear communication, and reliable follow-through.

Key Responsibilities

1. Turn discovery into clear plans and artifacts

• Participate in stakeholder and user discovery; document workflows, needs, constraints, and desired outcomes.
• Translate conversation and research into clear requirements, user stories, workshop plans, decision logs, product roadmaps, and next steps for the workstream owner.
• Maintain current use-case and action trackers so priorities, dependencies, and open questions stay visible.

2. Build: keep product and delivery work moving

• Maintain backlogs, requirements, roadmaps, and delivery artifacts as client needs and priorities change.
• Coordinate practical dependencies with client partners, designers, and engineers, such as data, access, calendars, and decisions.
• Run test sets or evaluation steps when needed; log failure modes and summarize evidence for review.

3. Enablement: prepare and deliver practical learning

• 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 how to use them, known limitations, and review needs.
• Gather participant feedback and update learning materials and follow-up actions based on what users need.

4. Make progress and outcomes visible

• Track delivery progress and adoption signals such as usage, realized business outcomes, and time savings; distinguish 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.

5. Work well across the delivery team

• 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.

Qualifications

Required

You should bring meaningful experience in at least one of the following areas. 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.
• 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.
• Ability to prepare clear learning materials, explain AI in practical terms, and help users apply new tools in their workflows.

Shared strengths

• Strong AI fluency: practical use of current AI tools and a working understanding of their capabilities, limitations,…