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.
Job Description
At Wise, our mission is money without borders — instant, convenient, transparent, and eventually free. We help people and businesses move money across borders. Delivering that mission requires operational services that are fast, accurate and scalable.
Our Customer Support (CS) and Know Your Customer (KYC) Operations teams are expanding their use of artificial intelligence (AI) to support colleagues and improve how work gets done. We’re looking for an AI Implementation Senior Manager to turn operational challenges into practical AI solutions for our global teams.
You’ll join Transformation, Governance and Strategy (TGS), the team that designs and delivers initiatives and governance frameworks to help Wise’s operations scale, and report to the Head of TGS.
Your mission
This is primarily an independent, hands-on builder role. You’ll spend most of your time designing, building, integrating and improving AI solutions. Your seniority will be reflected in technical judgement, ownership of delivery and your ability to influence across teams.
You’ll take solutions from opportunity discovery and prototype through deployment and ongoing improvement. Working with operational experts, Product and Engineering, you’ll ensure they fit Wise’s architecture, use reliable business data and deliver measurable value.
What you’ll do
Identify opportunities: Work with operational teams and TGS specialists to understand complex workflows and prioritise opportunities for AI assistance or automation.
Build and integrate solutions: Design and develop AI agents using approved platforms and custom code where needed. Map data flows, connect reliable knowledge sources and integrate outputs into existing tools without unnecessary manual workarounds or duplicate systems.
Assess and improve enterprise data readiness: Understand how operational data is created, defined and connected across Wise’s systems. Identify authoritative sources and assess their quality, completeness, freshness, accessibility and business context for each use case. Work with data and system owners to resolve gaps, clarify definitions and establish reliable data flows so AI agents can produce accurate, actionable results.
Deliver with partner teams: Work with operational experts and AI Champions to test solutions against real needs. Coordinate technical dependencies and deployment with Product and Engineering, and engage Privacy, Security and Compliance throughout delivery.
Monitor and improve: Maintain the agents you build, monitor their accuracy and reliability, and improve them as business needs and technology evolve.
Enable wider adoption: Document solutions, contribute to the central AI knowledge wiki and share reusable approaches that help colleagues build their capabilities.
Qualifications
Essential experience
Practical AI implementation: Demonstrable experience building AI agents or automations, including designing, testing and improving prompts and agent workflows.
Enterprise data fluency and readiness: You can navigate a complex enterprise data landscape and assess whether the available data is fit for an AI use case. You understand data ownership, lineage, business definitions and relationships across systems. You can identify missing context, inconsistent records and access constraints, then work with the right teams to address them.
Systems and data integration: You can use SQL, APIs and connectors to give AI agents reliable business context and integrate their outputs into operational workflows. You design data flows with appropriate permissions, maintainability and alignment with existing architecture.
Software development: Experience building tools or extending platforms when off-the-shelf solutions do not meet the need. You can turn prototypes into tested, documented and maintainable software.
AI and architecture judgement: An understanding of how large language models (LLMs) behave and fit into backend systems. You can evaluate outputs, recognise limitations and make design choices that support scalability and avoid unnecessary technical debt.
Independent delivery: A track record of taking ownership from problem definition through delivery. You build relationships, resolve dependencies and align your work with Product and Engineering’s technical direction.
Testing and iteration: Comfort working through ambiguity, testing ideas empirically and using what you learn to improve solutions.
Clear communication: The ability to translate operational needs into technical requirements and explain solutions clearly to technical and operational colleagues.
Desirable experience
Experience with platforms such as Credal, Gemini, Agentspace, NotebookLM, Codex, Replit, Claude.
Knowledge of Payments, Customer Support, Financial Crime or KYC operations.
Experience navigating enterprise data lakes, warehouses and lakehouses.
Experience using Google Apps Script or JavaScript to prototype operational solutions.
What success looks like
Your impact will be measured by the practical value your solutions deliver:
Operational impact: Measurable reductions in manual effort and cost per case, or increased capacity, while maintaining service quality and compliance.
Adoption and usefulness: Sustained use and positive feedback from the operational teams using your solutions.
Quality and reliability: Deployed agents meet agreed accuracy and reliability standards, with performance monitored and improved over time.
Salary for the role: £83000 to £110000 annually (+RSU's)
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.
Skills Required
- Demonstrable experience building, testing, and improving AI agents or automations, including prompts and agent workflows
- Experience navigating enterprise data landscapes and assessing data readiness, ownership, lineage, definitions, quality, and access constraints
- Experience using SQL, APIs, and connectors to provide business context to AI agents and integrate outputs into operational workflows
- Experience building tools or extending platforms with maintainable, tested, and documented software
- Understanding of LLM behavior and backend architecture, including output evaluation, limitations, scalability, and technical debt
- Track record of independently owning work from problem definition through delivery and resolving cross-functional dependencies
- Comfort with ambiguity, empirical testing, iteration, and continuous solution improvement
- Ability to translate operational needs into technical requirements and communicate solutions clearly
- Experience with platforms such as Credal, Gemini, Agentspace, NotebookLM, Codex, Replit, or Claude
- Knowledge of Payments, Customer Support, Financial Crime, or KYC operations
- Experience with enterprise data lakes, warehouses, or lakehouses
- Experience using Google Apps Script or JavaScript to prototype operational solutions
Wise Compensation & Benefits Highlights
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Equity Value & Accessibility — Equity is broadly accessible through RSUs granted to all employees in addition to salary, aligning rewards with company performance. This company‑wide ownership stance is consistently highlighted in the benefits descriptions.
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Leave & Time Off Breadth — Paid time off is notably generous, with a global minimum of 33 days and 36 days listed for U.S. locations. After four years, a six‑week paid sabbatical plus a £1,000 stipend further strengthens time‑away benefits.
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Wellbeing & Lifestyle Benefits — Lifestyle support includes work‑from‑anywhere for up to 90 days per year after six months, flexible working principles, and a 24/7 Employee Assistance Program. Extras like three annual “Me Days” and a professional‑development allowance add quality‑of‑life value.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
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Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.










