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 DescriptionOur Servicing Operations team is on a critical path to scale by accelerating our adoption of Artificial Intelligence. We are building a hybrid workforce where every team member is empowered by an AI 'Agent' working alongside them. To supercharge this effort, we're looking for a hands-on AI Implementation Specialist to join us and turn AI concepts into practical, impactful solutions for our global teams.
Your Mission
As the engine room for our operational AI adoption , your primary focus will be to bring our AI strategy to life by building the tools our teams need. You will:
Own the end-to-end lifecycle of building and deploying AI Agents. You will own the creation of AI agents from start to finish. This includes triaging requests from our internal teams, gathering requirements, and building robust solutions using platforms like Credal.ai, Gemini, and Google Agentspace.
Leverage your SQL skills to master the data. You will extract, transform, and load necessary data from various sources to train and inform our AI agents, ensuring they are accurate and context-aware.
Collaborate across the business to deliver robust solutions. You will work side-by-side with our "AI Champions" and operational experts to solve real-world problems, while proactively engaging with Privacy, Security, and Compliance to ensure your solutions are secure, compliant, and launched efficiently.
Iterate, Monitor, and Improve. You will be responsible for maintaining, monitoring, and continuously improving the agents you build to ensure they remain effective as our business and the technology evolves.
Scale your impact through documentation and best practices. You will document your solutions, contribute to our central AI knowledge wiki, and help upskill the wider organization by sharing your work.
What success looks like (KPIs)
Your impact will be measured by the practical value you deliver to our operations teams.
Solution Velocity & Throughput: The number of AI agents successfully built and deployed in response to business needs.
Operational Efficiency Gains: The quantifiable impact of your deployed agents, measured by metrics like total hours saved or reduction in manual tasks.
Adoption & Satisfaction: High usage rates and positive feedback from the operational teams using the agents you've built.
Accuracy & Reliability: The decision accuracy and calibration rate of the automated processes you implement.
This role is for you if you have…
We're looking for someone who is passionate about the practical application of AI and has a strong technical foundation.
Hands-on AI implementation experience. You have demonstrable experience building AI agents or automations and are an expert prompt engineer.
Expert SQL Proficiency. You are highly skilled in writing complex queries to extract and optimise datasets for AI processing.
A strong conceptual understanding of AI. You don't need to be a data scientist, but you must be able to intelligently discuss concepts like Prompts, Tokens, Context Windows, and the differences between major models (e.g., GPT, Gemini, Claude).
A proactive, problem-solving mindset. You have a proven track record of taking ownership, working collaboratively in a complex organization, and driving projects to completion.
Comfort with ambiguity and a bias for iteration. This is a highly experimental space. You are comfortable navigating uncertainty, grounding your approach in empirical testing, and embracing failure as a learning opportunity.
Excellent communication skills. You are proactive, clear, and concise, with the ability to translate complex operational needs into technical requirements.
Bonus points for:
Direct experience with our current toolset: Credal.ai, Gemini, NotebookLM, or Google Agentspace.
Subject-matter expertise in a core servicing area like Payments, Customer Support, Financial Crime, or KYC.
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.
Top Skills
What the Team is Saying
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.
