AI Deployment Manager

Eliza • Remote, US,

1d

About The Position

The AI Deployment Manager works with clients to turn business needs into practical AI solutions and measurable outcomes. The role may focus on Build—shaping and delivering AI products and workflows with engineering teams—or Enablement—helping people adopt AI through training, hands-on learning, and workflow development with client champions. Candidates are not expected to specialize equally in both areas, though experience across both is welcome.

The manager leads work aligned with their strengths and each engagement’s needs, collaborating closely with clients to understand how teams operate, use AI thoughtfully, and remain accountable for results. Eliza is AI-native, and the role uses AI tools across discovery, product definition, workflow building, training, and client communication while explaining their benefits and limitations. Client work can change as users and evidence reveal new needs, so thoughtful preparation, adaptability, and reliable follow-through are valued.

The position includes competitive compensation consisting of base salary and performance incentives tied to client outcomes, equity options, exposure to varied industries and high-impact AI problems, and optional travel for on-site client engagements. The manager owns meaningful AI work from discovery through delivery or adoption, works directly with client teams, partners with engineers and client leaders, and helps shape reusable delivery and enablement methods.

Requirements

• Meaningful depth in at least one of the Build or Enablement areas; experience across both is welcome but not required.
• Build: Product or delivery experience translating business needs into requirements and coordinating with engineering to move AI or software solutions toward launch.
• Build: Ability to assess feasibility, define acceptance evidence, and manage delivery tradeoffs as prototypes move toward production.
• Enablement: Experience in client enablement, training, learning and development, adoption, customer success, or change work.
• Enablement: Ability to facilitate practical learning and help users translate workflows into AI-supported practices and clear adoption measures.
• Strong AI fluency, including 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, including knowing 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.

Nice To Haves

• 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.

Responsibilities

• 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, and recommend what is ready to pursue.
• Align client stakeholders on priorities, target users, milestones, and measures of success.
• Translate business needs into product requirements, specifications, acceptance criteria, product roadmaps, and delivery plans for engineers.
• 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.
• Design and lead trainings, workshops, and office hours to help people apply AI in their daily work.
• Co-build, test, and refine prompts, skills, and workflows with client champions, clarifying limitations and review needs.
• Turn effective practices into learning materials, curricula, and reusable templates.
• Define success criteria with client experts, including for AI systems that require ongoing evaluation.
• Track product and adoption signals such as usage, realized business outcomes, and time saved, distinguishing measured results from early indications.
• Use evaluation results, participant feedback, and adoption evidence to improve solutions and follow-up.
• Manage scope, dependencies, risks, and client cadence while aligning business stakeholders, subject-matter experts, and technical teams.
• Communicate progress, decisions, and tradeoffs clearly; raise feasibility concerns and challenge low-value requests early.
• Prepare and facilitate executive steering committee meetings to share progress and shape future opportunities with clients.
• Package proven delivery methods, learning materials, and workflow assets for reuse across engagements.

Benefits

• Competitive compensation: base salary plus 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.
• Collaborative, mission-driven team passionate about the real-world impact of AI.
• Opportunity to own meaningful AI work from client discovery through delivery or adoption.
• Direct work with client teams on practical AI use cases and workflows.
• Partnership with engineers, client leaders, and subject-matter experts.
• Opportunity to help shape reusable product delivery and enablement methods across engagements.

What This Job Offers

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