Senior AI Deployment Manager, Finance

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 Senior AI Deployment Manager, Finance brings strong finance-domain experience to client work that applies AI to accounting and finance workflows. You will lead client discovery and delivery workstreams, turn unclear process needs into a practical implementation plan, and partner with Forward Deployed Engineers to move the work forward.

The priority areas are order-to-cash, month-end accounting close, and procure-to-pay. You should understand how finance teams operate and have implemented AI workflows in real work. Deep accounting process judgment matters more than AI specialization; you should be able to learn new tools quickly, explain their limits, and bring engineering in where technical decisions require it.

Eliza works AI-first and expects everyone in the company to use AI tools thoughtfully in their work. Client priorities move quickly, and the work can be ambiguous. You will receive ownership of a workstream, not a fixed script, and will be expected to communicate risks and tradeoffs early.

Key Responsibilities

1. Lead finance discovery and process mapping

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Run client sessions to understand the finance outcome, users, current process, systems, data, controls, exceptions, and pain points.

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Focus discovery on O2C, month-end close, and P2P; establish the facts needed to assess value and feasibility.

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Identify which process steps are suitable for AI, where conventional automation is a better fit, and where human judgment must remain.

1. Define a practical implementation plan

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Translate finance needs into product requirements, prioritized MVP scope, acceptance criteria, and a work plan an FDE can build against.

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Make dependencies, access needs, data quality, risks, and assumptions explicit.

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Recommend a sequence that balances business value, feasibility, timing, and quality.

1. Own the delivery workstream

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Manage scope, milestones, client decisions, risks, handoffs, and status through testing and client review.

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Partner closely with an FDE, keeping business requirements and technical decisions aligned without taking over engineering ownership.

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Evaluate workflow performance using agreed test cases and success criteria; surface failure modes and propose next steps.

1. Build client confidence and adoption

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Facilitate working sessions with finance SMEs and communicate progress and tradeoffs in clear language.

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Present concise updates that distinguish verified results from estimates or hypotheses.

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Help client teams understand the workflow, its limitations, review requirements, and operational handoffs.

1. Contribute to the finance delivery practice

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Support finance-focused pursuits and scope discussions with grounded process and implementation judgment.

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Coach Associates or teammates on client delivery and finance-workstream execution where assigned.

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Package reusable discovery questions, process maps, requirements patterns, and delivery lessons.

Qualifications

Required

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Strong finance-domain experience in finance transformation, program finance, corporate finance, or a related field.

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Practical knowledge of at least one of order-to-cash, month-end close, or procure-to-pay. Experience in AP/AR, invoicing, ERP, or finance systems is relevant.

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Evidence of implementing AI-supported workflows in real work; casual AI tool use alone is not enough.

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Ability to lead client-facing discovery and delivery, structure ambiguous problems, and own work through measurable review.

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Can translate finance process requirements into clear implementation considerations and partner effectively with engineers.

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Working understanding of AI capabilities and limitations, with sound judgment about human review and operational risk.

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Strong writing, presentation, stakeholder management, and prioritization skills.

Preferred

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Finance transformation consulting or professional-services delivery experience.

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FP&A, program finance, or analytical experience.

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Controller, CPA, or accounting-operations background.

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ERP implementation, finance automation, or finance-focused AI product experience.

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Experience in a PE-backed company.

What We Offer

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Competitive compensation (base salary + performance incentives tied to client outcomes).

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Equity options in a growing AI services company.

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Exposure to a wide range of industries and high-impact AI problems.

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Travel opportunities for on-site client engagements (if desired)

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Direct client ownership of finance AI work from discovery through implementation planning and outcome review.

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Close partnership with engineers and finance leaders on real operational problems.

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The opportunity to shape reusable methods for finance AI delivery.

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Variety across finance processes, systems, and client environments.

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A high-ownership role with room to grow as the OCFO practice develops.