Senior AI Deployment Manager, Finance

Job 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. ### 4. Build client confidence and adoption - Facilitate working sessions with finance SMEs and communicate progress and tradeoffs in clear language. - Present concise updates that distinguish verified results from estimates or hypotheses. - Help client teams understand the workflow, its limitations, review requirements, and operational handoffs. ### 5. Contribute to the finance delivery practice - Support finance-focused pursuits and scope discussions with grounded process and implementation judgment. - Coach Associates or teammates on client delivery and finance-workstream execution where assigned. - Package reusable discovery questions, process maps, requirements patterns, and delivery lessons. ## Qualifications ### Required - 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. ### Preferred - 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. ## What We Offer - 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 client ownership of finance AI work from discovery through implementation planning and outcome review. - Close partnership with engineers and finance leaders on real operational problems. - The opportunity to shape reusable methods for finance AI delivery. - Variety across finance processes, systems, and client environments. - A high-ownership role with room to grow as the OCFO practice develops.