Senior AI Deployment Manager, Finance
- Compensation
- Not disclosed
- Location
- United States
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Not specified
- Posted
Skills
Must have
- Strong finance-domain experience in finance transformation, program finance, corporate finance, or a related field.
- 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.
- Evidence of implementing AI-supported workflows in real work; casual AI tool use alone is not enough.
- Ability to lead client-facing discovery and delivery, structure ambiguous problems, and own work through measurable review.
- Can translate finance process requirements into clear implementation considerations and partner effectively with engineers.
- Working understanding of AI capabilities and limitations, with sound judgment about human review and operational risk.
- Strong writing, presentation, stakeholder management, and prioritization skills.
Nice to have
- Finance transformation consulting or professional-services delivery experience.
- FP&A, program finance, or analytical experience.
- Controller, CPA, or accounting-operations background.
- ERP implementation, finance automation, or finance-focused AI product experience.
- Experience in a PE-backed company.
Full description
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
- Run client sessions to understand the finance outcome, users, current process, systems, data, controls, exceptions, and pain points.
- Focus discovery on O2C, month-end close, and P2P; establish the facts needed to assess value and feasibility.
- Identify which process steps are suitable for AI, where conventional automation is a better fit, and where human judgment must remain.
2. Define a practical implementation plan
- Translate finance needs into product requirements, prioritized MVP scope, acceptance criteria, and a work plan an FDE can build against.
- Make dependencies, access needs, data quality, risks, and assumptions explicit.
- Recommend a sequence that balances business value, feasibility, timing, and quality.
3. Own the delivery workstream
- Manage scope, milestones, client decisions, risks, handoffs, and status through testing and client review.
- Partner closely with an FDE, keeping business requirements and technical decisions aligned without taking over engineering ownership.
- Evaluate workflow performance using agreed test cases and success criteria; surface failure modes and propose next steps.