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Principal AI Deployment Manager

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🔥 1 minute ago

🇺🇸 United States – Remote

⏰ Full Time

đź”´ Lead

🤖 Artificial Intelligence

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Eliza

11 - 50 employees

Founded 2025

🤖 Artificial Intelligence

đź’Ľ Consulting

🏢 Enterprise

Artificial Intelligence • Consulting • Enterprise

Eliza is an AI-native consulting firm that helps enterprises turn frontier generative AI (notably ChatGPT/OpenAI) into measurable production impact. They embed AI architects and enablement leaders into client teams to build AI fluency (Fusion), redesign and automate repeatable processes into AI-assisted workflows (Flow), and design and ship production-grade AI systems, agents, copilots, and integrations (Forge). Eliza focuses on enterprise deployments, capability transfer to client teams, and delivering measurable ROI (100+ deployments and client case results noted on their site).

đź“‹ Description

• Lead finance process discovery with controllers, accounting teams, and client subject-matter experts • Map order-to-cash, month-end close, and procure-to-pay workflows, including systems, controls, handoffs, and exceptions • Establish current-state baselines and define successful outcomes • Assess process fit, data readiness, risk, and required human review or approval • Translate accounting workflows and policy requirements into product requirements, decision rules, acceptance criteria, roadmaps, and test cases • Prioritize opportunities by feasibility, finance impact, data quality, and implementation effort • Recommend where AI is useful, standard automation is sufficient, or a process is not ready • Partner with Forward Deployed Engineers to shape MVP plans, clarify dependencies, and make scope, quality, and timing tradeoffs • Review workflow behavior against representative finance cases, edge conditions, exceptions, reconciliations, and audit evidence • Track model limitations, data quality, access controls, and production-readiness risks from prototype to deployment • Define evaluation criteria and business outcomes and track results against agreed baselines • Present findings, distinguish measured results from hypotheses, and recommend improvements or next tests • Build client confidence through accurate communication, practical training, and clear handoffs • Turn client lessons into reusable process maps, requirements patterns, evaluation methods, and implementation guidance • Contribute controller expertise to finance discovery, solution design, and pursuit planning • Raise delivery or client risks early and help maintain high standards for finance AI work

🎯 Requirements

• CPA background and substantial controller or controllership experience • Deep experience with ERP, accounting systems, or finance systems implementations and process change • Strong working knowledge of core accounting and finance processes and underlying systems, including order-to-cash, month-end close, or procure-to-pay • Evidence of implementing AI-supported workflows in finance or accounting, with practical understanding of AI capabilities and limitations • Ability to translate accounting policy, controls, exceptions, and system behavior into requirements engineering teams can implement and test • Client-facing communication skills and judgment to ask precise questions, challenge assumptions, and explain tradeoffs clearly • Ownership of outcomes through discovery, delivery, evaluation, and client review • Preferred: Controller experience in a PE-backed company • Preferred: Experience with AI-native ERP or finance automation platforms, accounting agents, or ERP integrations • Preferred: Finance transformation consulting or work across multiple priority finance processes • Preferred: Experience defining evaluation methods and controls for AI systems used in finance • Legally authorized to work in the United States • Must disclose whether employment visa sponsorship is required now or in the future

🏖️ 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) • Direct work with finance leaders on practical AI deployments that affect core accounting workflows • Close partnership with experienced engineers and client subject-matter experts • Opportunity to shape how controller and accounting expertise informs AI delivery • Meaningful ownership from discovery through measured client outcomes • Opportunity to shape reusable methods for finance AI delivery • Variety across finance processes, systems, and client environments • Leadership role within a high-growth OCFO practice

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