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Based on 240 similar postings.
Employer
About Wise
Wise (formerly TransferWise) is a global technology company specializing in international money transfers and multi-currency accounts, offering transparent low-cost foreign exchange for individuals and businesses. Industry: Financial Technology & International Payments
As the Engineering Lead - Wise AI Assistant Platform, you will join the Wise Assistant team to build a conversational AI serving as a central interface for managing money. You will lead a small, senior engineering team to develop production-grade LLM systems while shaping the technical vision regarding architecture, evaluation, and research integration. Your daily work involves collaborating with Data Science, Product Management, Analyst, and Prompt Engineering functions to move beyond experiments into large-scale production. The role requires hands-on expertise in Java, REST APIs, microservices, distributed systems, and CI/CD pipelines. You must possess deep knowledge of LLM engineering, including RAG architectures, vector databases, embeddings, prompt engineering, orchestration patterns, tool use, and safety guardrails. Experience with TypeScript or transformer architectures is a plus as you solve complex fintech problems using advanced AI technologies.
Lead a small team of senior engineers building production-grade LLM systems.
Define the technical vision for AI architecture, evaluation, and research integration.
Design and implement scalable system architectures using Java and microservices.
Develop RAG architectures, vector databases, and prompt engineering strategies.
Implement guardrails and safety measures for large-scale conversational AI.
Prototype new AI approaches based on current research to move into production.
Collaborate with Data Science, Product Management, and Prompt Engineering teams.
What we're looking for
You must have at least 2 years of experience leading engineering teams, ideally including senior engineers.
You must have hands-on technical experience in Java and modern technology stacks like REST APIs, microservices, distributed systems, and CI/CD pipelines.
You must possess a solid understanding of LLM engineering, including RAG architectures, vector databases, prompt engineering, and evaluation methods.
You must demonstrate excellent collaboration skills across different functions and teams.
You should have a passion for AI and a desire to push boundaries on production systems at scale.
TypeScript experience is preferred.
Deeper knowledge of AI fundamentals, such as transformer architectures and fine-tuning, is preferred.