Lead FullStack Engineer (AI)

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.

You will be:

We are looking for a hands-on Technical Lead who combines strong software engineering skills with technical leadership, staying actively involved in writing production code while guiding a high-performing team of engineers.

You will be building modern, cloud-native digital products in the financial services sector, including AI-powered features such as conversational voice and chat experiences. Working in fast-paced, agile delivery teams, you will collaborate closely with product, design and consulting partners to deliver scalable, high-quality solutions.

This role combines hands-on development, architectural ownership and team leadership. You will be responsible for driving technical decisions, setting engineering standards and ensuring efficient delivery while remaining actively involved in complex frontend, backend and AI integration work.

You will be:

the role involves working closely with a US-based client, requiring availability until 6:00 PM CET daily and until 9:00 PM CET twice a week to accommodate collaboration across time zones,

developing complex frontend, backend and AI integrations while leading by example through hands-on coding,

designing and implementing technical solutions within a domain-driven architecture, including APIs and event-driven integrations,

leading the development of AI-powered features using Claude, AWS Bedrock and LangGraph, including orchestration, guardrails and evaluation,

collaborating with designers to translate Figma designs into pixel-accurate, accessible user interfaces,

establishing engineering standards for code reviews, testing and AI-assisted development,

driving CI/CD pipelines using GitHub Actions and infrastructure as code using AWS CDK,

implementing and maintaining automated testing practices across unit, integration and end-to-end testing,

mentoring engineers, removing technical blockers and maintaining high engineering standards during agile delivery cycles,

collaborating with delivery leads, architects and product owners on technical decisions, risks and trade-offs,

leading squads of 8-20 engineers while remaining actively involved in software development.

Your profile:

the role involves working closely with a US-based client, requiring availability until 6:00 PM CET daily and until 9:00 PM CET twice a week to accommodate collaboration across time zones,

expert-level knowledge of React, Next.js and TypeScript,

strong experience translating Figma designs into production-ready frontend applications,

hands-on experience developing backend solutions using TypeScript and AWS serverless services, including Lambda, API Gateway, EventBridge, Step Functions and DynamoDB,

strong API design skills and experience with event-driven integrations,

production experience building LLM-powered applications, ideally using Claude through AWS Bedrock,

practical experience with AI agent orchestration using LangGraph, including RAG, tool use, prompt design, guardrails and evaluation,

experience building CI/CD pipelines with GitHub Actions and managing infrastructure as code using AWS CDK,

experience implementing automated unit, integration and end-to-end tests,

daily, effective use of AI-assisted coding tools such as Claude Code, GitHub Copilot or Cursor, with an understanding of safe and productive usage in team environments,

hands-on experience delivering software in agile teams,

proven experience leading squads of 8-20 engineers while maintaining a hands-on technical role,

practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery,

Work from the European Union region and a work permit are required.

Nice to have:

experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work.

• interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.