Director, FinTech Operations & AI Transformation
Listed on 2026-06-21
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IT/Tech
AI Engineer (Applied/Software)
Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
AboutThe Role
We are looking for a transformational operator to lead the next chapter of our Financial Services Operations organization. This is not a steady-state management role. We are at an inflection point — transitioning from a human-led, high-touch model to a high-touch, agentic human-in-the-loop model — and we need a leader who can drive that transformation while simultaneously holding the line on the SLAs that underpin some of Toast's highest-NPS products.
Reporting directly to the Head of Embedded Finance, the Director of Operations & AI Transformation will own end-to-end operational delivery across Embedded Finance - Banking, Lending, Collections, Leasing, Spend Management, and Financial Management. You will manage a team of 30+ managers and operators through an AI transformation roadmap, and redefine what "great" looks like in financial services operations.
What You'll Own Operational Leadership & Performance- Own SLA performance and quality outcomes across all Embedded Fintech product verticals.
- Build and maintain the operational dashboards, capacity models, and escalation frameworks needed to run a high-performing 30+ person organization.
- Partner with Product and R&D to reduce the operational burden caused by gaps between applications and disparate systems — your goal is to eliminate the manual bridging work, not just manage it.
- Champion a white-glove service standard: every customer interaction should feel intentional, expert, and high-trust.
- Lead the design and execution of an "Ops Engine" built on agentic protocols — AI-powered workflows that handle routine, repeatable tasks so your team can focus on high-complexity, high-value work.
- Partner with R&D to identify where LLM-based tooling, intelligent routing, and automated decisioning can be embedded directly into operational workflows.
- Define a phased AI transformation roadmap with clear milestones, risk controls, and measurable productivity outcomes.
- Serve as the internal expert and advocate for agentic AI adoption in Fin Tech operations — educating the broader organization on what's possible and building the internal credibility to drive adoption.
- Directly manage a layer of operational managers; develop them into confident, data-driven leaders capable of running their verticals with increasing autonomy.
- Build a coaching culture that prepares the broader team of operators for an AI-augmented future — upskilling, reskilling, and redeploying talent as the nature of the work evolves.
- Navigate the human side of transformation with empathy and transparency: help the team understand what is changing, why it matters, and what their role looks like on the other side.
- Synthesize operational performance data into executive-level insights; bring a clear point of view to senior leadership on where to invest, where to simplify, and where to automate.
- Partner cross-functionally with Product, R&D, Risk, Compliance, and Finance to ensure operational requirements are reflected in product roadmaps and system architecture decisions.
- Define the long-term organizational design for Operations — the right roles, structures, and skills for a high-touch, agentic team.
- Turn Operations into a growth engine for Toast Embedded Finance. Bringing the voice of the customer and a strong sense of hospitality to grow our products and deliver success for the customer.
- Progressive operations leadership experience, with experience managing managers in a high-volume, SLA-driven environment.
- Demonstrated experience leading teams through significant operational or technology transformation — not just participating in it, but owning the outcome.
- Deep AI fluency: you understand the current landscape of LLMs, agentic workflows, and automation tooling well enough to evaluate trade-offs, prioritize use cases, and hold technical partners accountable. You don't need to build the models, but you need to know what they can…
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