VP, AI Innovation

The VP, AI Solutions will serve as ATLAS’s forward deployed engineer (FDE) to the firm’s business desks - CRE, Residential, Auto/Equipment, Transportation, Energy, Infrastructure, Fund Finance, and others - partnering directly with desk and operations leads to understand how deals get done today and where AI can meaningfully improve the work. This is not a role focused on replicating existing processes step-for-step in an AI wrapper; it is a role focused on questioning and redesigning workflows so that AI is embedded where it adds the most value.

The VP will work side-by-side with desk professionals to map current-state workflows, identify friction points and manual handoffs, and design target-state processes that combine automation, augmentation, and human judgment appropriately. The VP will build working prototypes directly with desk teams, iterate quickly based on real usage, and partner with the Director, AI Innovation and the broader technology organization to move validated solutions into governed, production-ready capabilities including contributing reusable components to the firm’s AI skills catalog. This position is based in New York.

Financial services experience is essential, along with the judgment to know when a process should be redesigned rather than merely automated, and the communication skills to bring skeptical desk stakeholders along.

Primary Responsibilities

• Desk Engagement & Discovery
  • Embed directly with business desks CRE, Residential, Auto/Equipment, Transportation, Energy, Infrastructure, Risk, Treasury, Accounting and others to learn existing workflows, tools, and pain points firsthand.
  • Run structured discovery sessions with desk and operations leads to surface high-friction, high-volume, or error-prone processes suited to AI-enabled redesign.
  • Distinguish opportunities for genuine workflow and process redesign from requests to simply automate an existing manual step.
  • Partner with desk leads to prioritize opportunities based on business impact, feasibility, and readiness for change.
• Solution Design & Prototyping
  • Design and build working prototypes and proof-of-concepts directly with desk teams, iterating quickly based on real feedback and usage.
  • Apply a forward deployed engineering approach: sit with the business, build fast, and validate against real deal work rather than hypothetical requirements.
  • Guide desk and ops leads in authoring their own reusable skills and workflows, consistent with the principle that desks own the domain content.
  • Ensure prototypes meet baseline security, data-handling, and governance expectations before they reach production consideration.
• Workflow & Process Redesign
  • Map current state processes end-to-end and identify where AI should change the shape of the workflow, not just the tool used to execute it.
  • Partner with desk leadership to redesign processes around AI-native capabilities, rather than treating AI as a 1:1 replacement for existing manual steps.
  • Recommend where roles, handoffs, and controls should shift as a result of redesigned workflows, and flag clearly where redesign is not the right answer.
• Deployment & Adoption
  • Transition validated prototypes into governed, production-ready solutions in partnership with the Director, AI Innovation and technology, security, and platform teams.
  • Drive change management and training with desk teams to ensure adoption, understanding of capabilities and limits, and sustained usage.
  • Monitor deployed solutions for performance, drift, and usage, feeding learnings back into the firm’s AI governance program.
• Skills Catalog & Enterprise Reuse
  • Contribute reusable skills, prompts, and workflow patterns to the firm-wide Claude skills catalog, tagged across firm-wide, ABF-primitive, desk-specific, and deal-specific layers.
  • Identify overlap and duplication across desks and route reusable patterns into shared, discoverable components rather than one-off, siloed chats.
  • Support discovery, deprecation, and ownership-succession practices so catalog content stays current and trustworthy.
• Cross-Functional Partnership
  • Act as the connective tissue between business desks and the AI Innovation, technology, data, and architecture teams.
  • Partner with legal, compliance, risk, and security on responsible use, data handling, and governance considerations specific to each desk’s solutions.
  • Communicate solution value, tradeoffs, and redesign recommendations to desk leadership and senior stakeholders in clear, practical language.

Qualification and Experience

• Required
  • 7+ years of experience in technology, product, or process/workflow transformation roles, including hands-on experience building with AI/ML or LLM-based tools.
  • Background working in financial services, ideally within asset-based finance, structured credit, or an adjacent lending/capital markets business.
  • Demonstrated experience as a forward deployed engineer, solutions engineer, or similar embedded technical role working directly with business stakeholders.
  • Strong process and workflow design skills. Ability to map a current-state process, question its assumptions, and design a genuinely redesigned target state rather than a like-for-like automation.
  • Working knowledge of modern AI technologies, including LLMs, prompt engineering, and agent/skill-based frameworks.
  • Hands-on experience building with RAG (retrieval-augmented generation) architectures and agentic frameworks (e.g., LangChain, LangGraph, or similar), including vector stores, tool/function calling, and multi-step agent orchestration.
  • Experience partnering with non-technical business stakeholders to translate ambiguous problems into scoped, buildable AI solutions.
  • Excellent communication and relationship-building skills, with the credibility to work directly with desk and operations leads.
  • Comfort operating with significant autonomy in a fast-paced, high-growth environment.
  • Ability to travel to or spend regular time with desk teams as needed to maintain close engagement.

• Preferred
  • Experience with asset classes such as CRE, residential, auto/equipment, transportation, energy, infrastructure, or fund finance.
  • Experience contributing to or building an internal tools/skills catalog or reusable component library.