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EXL

Analyzes business data and runs outsourced operations

Vice President Pre-Sales & AI Solutions - Agentic Finance Suite

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$200k - $250k

About the Job

Requirements

  • The candidate should have 12–15 years of overall experience, including 10+ years in the US leading consulting, solutioning, F&A SaaS, AI, and Agentic AI solution sales for enterprise Finance organizations.
  • The candidate should have deep working familiarity with Procure-to-Pay, Order-to-Cash, and Record-to-Report processes and common accounts payable, accounts receivable, and Record-to-Report pain points.
  • The candidate should have hands-on experience with enterprise ERP environments such as SAP S/4HANA, Oracle Fusion, Coupa, or Ariba in a client-facing or implementation context.
  • The candidate should be able to discuss Finance KPIs including DPO, DSO, straight-through processing rates, three-way match accuracy, close cycle time, reconciliation accuracy, journal entry automation, and working capital impact.
  • The candidate should have prior involvement selling or solutioning AI and Agentic AI-powered Finance products, including intelligent document processing, machine-learning-based matching, autonomous workflow agents, human-in-the-loop exception handling, orchestration layers, and exception management automation.
  • The candidate should have sufficient technical grounding to explain what AI solutions can and cannot do without relying on a solutions architect for every difficult question.
  • The candidate should be able to sell Agentic AI as a business capability and connect autonomous agents, workflow intelligence, copilots, and AI-assisted decisioning to measurable Finance outcomes across AP, AR, and R2R.
  • The candidate should be familiar with how AI capabilities are packaged and positioned in the Finance technology market, including key vendors and platform players.
  • The candidate should have experience engaging CFO-, VP Finance-, and Controller-level stakeholders and building credibility through specific knowledge.
  • The candidate should be able to explain complex AI concepts to Finance audiences accurately and produce proposals, executive summaries, and point-of-view content independently.
  • The candidate should have owned a sales pipeline, including forecasting, deal progression, and closing accountability.
  • The candidate should have experience leading multi-stakeholder sales cycles in Finance technology or BPS, from qualification through commercial agreement.
  • The candidate should be able to work in a matrixed environment and align delivery, product, and account teams toward shared outcomes.
  • The candidate should have a track record of converting first engagements into longer-term client relationships.
  • New York Tri-State area presence is preferred, with the ability to engage enterprise clients across the US through in-person and hybrid executive discussions.
  • The candidate should have demonstrated experience selling to or advising CFO-organization stakeholders, including CFOs, VP Finance leaders, Controllers, or Treasurers.
  • Direct experience with P2P, O2C, close, consolidation, reconciliation, or reporting transformation programs is a strong plus.
  • The candidate should be familiar with AI and Agentic AI Finance solutions such as IDP, intelligent matching, exception management, autonomous workflow agents, cash application automation, reconciliations, close orchestration, journal entry automation, and financial reporting automation.
  • The candidate should have experience with ERP platforms used in enterprise Finance environments, such as SAP S/4HANA, Oracle Fusion, Coupa, or similar platforms.
  • The candidate should be able to build and manage a sales pipeline, including forecasting and opportunity management.
  • The candidate should have strong written and verbal communication, proposal, and presentation skills.
  • A bachelor's degree in business, finance, engineering, or a related field is required.

Responsibilities

  • Build and manage a healthy funnel of AP, AR, and R2R opportunities, working with account teams and industry leaders to identify opportunities for EXL Finance AI solutions.
  • Track deal progress, flag risks early, and determine when to escalate or pivot.
  • Lead client conversations with VP, Controller, and CFO stakeholders, translate AI capabilities into business value, and build relationships that support long-term partnerships.
  • Lead deal scoping and structuring by defining the problem, proposed approach, and success measures.
  • Run discovery sessions, build business cases, and architect credible and deliverable proof-of-concepts.
  • Present EXL responses to Finance AI RFIs and RFPs, write clear proposals, select appropriate positioning, and position EXL to win.
  • Represent EXL in the market at industry events, in analyst conversations with Gartner, Everest, and ISG, and through point-of-view papers and client workshops.

Desired Qualifications

  • An MBA or CA is advantageous.
  • Strong functional knowledge of AP, AR, and R2R processes and direct experience with P2P, O2C, close, consolidation, reconciliation, or reporting transformation programs are a strong plus.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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