
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 Associate AI Product Manager is the execution engine of the AI PM function. While the AI PM owns scoping, strategic direction, and executive relationships on an account, the Associate owns the tactical delivery that makes those engagements run: trainings delivered, skills built, workshops executed, backlogs maintained, and progress made visible. This is a hands-on role for someone with strong AI fluency who wants to learn the full AI PM craft by delivering inside real engagements from week one.
Eliza AI PMs are expected to deliver both of our core engagement types, and Associates support delivery in both:
Forge (production AI system delivery): The Associate supports the AI PM and forward-deployed engineers—maintaining the use case backlog, documenting requirements, running eval execution, and keeping delivery unblocked.
Fusion (workforce enablement): The Associate is hands-on-keyboard in delivery—running trainings, building and refining skills with client champions, executing persona workshops, and tracking adoption.
Associates are staffed across both lanes based on account needs and development goals, with coaching from the AI PMs they support.
Deliver one-to-many trainings and hands-on, persona-specific workshops for client teams, from analysts to executives.
Build, test, and refine custom skills, prompts, and workflows with client champions; turn what works into repeatable curriculum.
Conduct persona and use-case interviews with client stakeholders to surface high-value workflows for workshops and skills.
Track adoption signals throughout the engagement: usage depth, use-case realization, and time savings—and flag what the data says.
Maintain the scored use case backlog: keep feasibility, data readiness, and priority current as discovery evolves.
Document requirements from client working sessions into structured inputs the AI PM can shape into specs.
Execute evals: run test sets, log failure modes, and summarize results so quality calls can be made quickly.
Run down blockers—access, data, calendars, approvals—so FDEs and the AI PM stay focused on the build.
Prepare executive readout materials: progress, metrics, risks, and next steps—short, honest, and outcome-oriented.
Keep engagement artifacts current: roadmaps, status trackers, meeting notes, and action items across concurrent workstreams.
Coordinate scheduling and logistics across client stakeholders, FDEs, and Eliza leadership.
Contribute to Eliza's reusable delivery assets: training curricula, skill libraries, workshop templates, and playbooks.
Track new model and product releases relevant to active engagements and surface what matters to the team.
Trainings and workshops run on schedule and clients ask for more of them.
Skills built with client champions get used after the workshop ends—adoption data proves it.
Backlogs, trackers, and readouts are current without being chased.
The AI PMs supported by this role spend measurably more time on scoping and strategy—and say so.
Within 6–12 months, this person is credibly stepping into AI PM scope on smaller engagements.
1–3 years in consulting, customer success, enablement/L&D, or product—client-facing delivery experience required.
Strong AI fluency: daily working use of frontier tools (ChatGPT, Claude, or similar), a working mental model of what current models can and cannot do, and the habit of updating it as the field moves.
Facilitation and presentation skills—comfortable teaching a room of skeptical analysts or walking an executive through a demo.
Highly organized under load: able to run parallel workstreams across multiple accounts without dropping threads.
Strong written communication—clear meeting notes, clean readouts, no jargon, no overselling.
Comfortable in ambiguity; takes ownership of loosely defined work and asks sharp questions early.
Hands-on experience building prompts, custom GPTs/skills, or lightweight automations—not just using AI, but shaping it.
Experience designing training content or adult learning programs.
Exposure to enterprise software delivery: sprints, backlogs, requirements documentation, or QA/eval work.
Familiarity with a functional domain Eliza serves (finance/office of the CFO, private equity operations, healthcare).
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.