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Salary
$154k – $201k per year
Location
In office (London)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Wise is a British financial technology company founded in 2011 by two Estonians who were frustrated by the cost of moving money between pounds and euros. It built a network of local bank accounts in each market so that most transfers never cross a border, publishes the mid-market exchange rate with an explicit fee, and has extended the model into multi-currency accounts, debit cards, business payments and an infrastructure product that banks resell. The company listed directly on the London Stock Exchange in 2021 and moves tens of billions of pounds for millions of personal and business customers each quarter.

Wise is a global technology company, building the best way to move and manage the world’s money.

Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.

For everyone, everywhere.

More about our mission and what we offer.

As AI Delivery Lead for Finance, you will plan and lead our first AI deployments, establish the reusable delivery and governance capability behind them, and shape the permanent Finance AI Delivery function. This is a new and exciting opportunity for an experienced individual to get hands on with delivery, while setting the direction and building out this new function over the longer term.

This is a high-impact, cross-functional leadership role. You will turn an ambiguous opportunity into a clear strategy and sequenced portfolio, stay close enough to delivery to unblock the hardest work, and build confidence that Finance AI solutions are valuable, reliable and controlled.

You will work within a centrally governed, federated model: partnering with Finance AI Champions to identify opportunities, while Finance process owners remain accountable for business outcomes, data, assumptions, human review and operational readiness.

What you will do

  • Set the direction: define and communicate the Finance AI strategy, delivery roadmap, standards and operating approach, making clear choices about what Finance should build, buy or enable locally

  • Own the opportunity portfolio: identify and size Finance workflows suitable for AI automation, then prioritise them using value, risk, readiness and delivery complexity

  • Lead the first deployments: select and design an initial Accounting-focused pilot and lead it end to end, from process discovery and control design through implementation, operation and evaluation

  • Make outcomes measurable: set success, failure and stop criteria before delivery begins, covering expected benefits, accuracy, control performance, adoption and the conditions for redesigning or retiring a solution

  • Build reusable capability: create and maintain reusable prompts, skills, workflow templates, data context and implementation patterns so each deployment makes the next one faster and safer

  • Set the production bar: define when standalone tools are appropriate and when repeatable or material workflows need a managed or agentic platform, with clear expectations for access, versioning, logging, monitoring, evidence and rollback

  • Stay technically hands-on: prototype and inspect solutions when needed, including writing small Python scripts, calling Model Context Protocol (MCP) servers and other tools, and building no-code agents to test ideas and unblock delivery

  • Lead governance through delivery: partner with Risk & Controls and process owners to embed human review, segregation of duties, IUC/EUC requirements, regulatory considerations and independent challenge where appropriate

  • Create alignment across Wise: secure and project-manage contributions from Accounting, Controls, Analytics, Data Science, Engineering, Product and Platform when priorities, dependencies and trade-offs compete

  • Build the team: determine the capabilities, roles and capacity required for a permanent Finance AI Delivery function; hire, coach and empower the team as it grows

  • Learn and scale: monitor deployed solutions, manage issues and performance drift, share evidence of what worked and failed, and recommend what Finance should scale next

Qualifications - what we're looking for

  • Strategic depth: you have set and delivered a long-term strategy in a complex or emerging domain, turning high ambiguity into explicit choices, sequenced work and measurable results

  • Applied AI delivery experience: you understand modern AI concepts and have hands-on experience working with or automating AI solutions, including prompts, tools or agents, evaluation and workflow integration

  • Judgement in a controlled environment: you can balance speed, benefit, reliability, data sensitivity and risk, and you know how to make human accountability and evidence part of the solution rather than an afterthought

  • Influence across boundaries: you communicate difficult problem statements and trade-offs concisely, build trust with senior stakeholders and create alignment across teams without relying only on formal authority

  • Organisational leadership: you can shape a new function, define clear responsibilities, make hiring decisions, coach specialists and create the conditions for others to deliver at a high standard

  • Commercial and operational thinking: you use data and practical economics to size opportunities, assess build-versus-buy choices and keep delivery accountable for real Finance outcomes

Nice to have

  • Senior delivery leadership: you have led complex cross-functional programmes with material operational, financial or regulatory consequences and can move fluently between strategy and implementation detail

  • Practical technical fluency: you are reasonably technical and comfortable writing or adapting Python scripts, connecting to and calling MCP servers and tools, and building no-code agents yourself; you do not need to be a software engineer, but you can prototype, investigate and challenge technical choices credibly

  • Finance domain knowledge: experience in Accounting, FP&A, Reporting, Treasury, Tax, Controlling or another regulated Finance environment

  • Controls experience: familiarity with SOX-relevant processes, EUC/IUC expectations, audit evidence, segregation of duties or model and AI risk management

  • Production AI knowledge: experience designing behavioural evaluations, guardrails, observability, incident response, safe rollback or cost and latency controls for AI workflows

  • Platform and vendor judgement: experience evaluating AI platforms or vendors and protecting long-term value by managing integration, portability and lock-in risks

For everyone, everywhere. We're people building money without borders - without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.

Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

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