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Xebia

Principal Fullstack Architect (AI & Agentic Systems)

Posted Yesterday
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Remote
Hiring Remotely in Hungary
Expert/Leader
Remote
Hiring Remotely in Hungary
Expert/Leader
Lead architecture and hands-on development of an AI-native underwriting platform. Design scalable backend services in Python, integrate with React/TypeScript frontends, promote engineering standards, implement observability and security, and use AI-assisted development tools to improve productivity while mentoring the team and driving the platform from MVP to production.
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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. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

About project:


We are looking for a Senior AI Software Engineer to join a project delivered for our international client operating in the insurance technology sector. The client is building a next-generation AI-native underwriting platform and is looking for an experienced engineer to help scale the product from MVP into a production-grade system.

This role is a great opportunity to join a small, highly collaborative engineering team building AI-first software from the ground up. You will act as a technical leader for AI-assisted software development, helping define engineering standards, improve developer productivity, and shape the technical direction of the platform while remaining deeply involved in hands-on software development.

The project combines modern backend engineering, AI-native application development, LLM-powered workflows, and platform engineering within a fast-moving product environment. You will work closely with senior engineers and product stakeholders to build scalable, secure, and observable systems while leveraging AI coding assistants as part of the daily development process.

You will be:
  • design, develop, and maintain core backend services using Python,
  • contribute to the architecture and technical direction of an AI-native underwriting platform,
  • act as a technical lead for AI-assisted software development within the engineering team,
  • build scalable, secure, observable, and production-ready software solutions,
  • collaborate with frontend engineers on integrations with React and TypeScript applications,
  • define and promote engineering standards, development workflows, and software quality practices,
  • leverage AI coding assistants to improve engineering velocity, code quality, and developer productivity,
  • contribute to system architecture, technical design, and platform evolution,
  • build internal engineering tooling and developer productivity solutions,
  • support technical decision-making while remaining highly hands-on in software development,
  • collaborate closely with product, engineering, and business stakeholders in an iterative product environment,
  • mentor team members through technical leadership, code reviews, and knowledge sharing,
  • help scale the platform from MVP to a robust enterprise-grade product,

Your profile:

  • extensive commercial experience developing production software using Python,
  • strong understanding of TypeScript and modern software engineering practices,
  • familiarity with React and frontend application architecture,
  • strong experience designing scalable software systems and distributed architectures,
  • production mindset with experience building reliable, maintainable, and scalable applications,
  • strong understanding of application security and secure software development practices,
  • experience implementing observability, monitoring, and operational best practices,
  • proven experience delivering production-grade software throughout the full software development lifecycle,
  • strong ownership mentality with the ability to independently drive technical initiatives,
  • comfortable working in fast-changing environments with evolving requirements and ambiguity,
  • practical experience using AI-assisted development tools as part of daily engineering work,
  • excellent communication and collaboration skills,
  • strong software engineering fundamentals and system design capabilities,

  • 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 building applications with LangGraph,
  • experience working with LangChain,
  • experience designing and implementing agentic AI workflows,
  • hands-on experience using Claude Code,
  • hands-on experience using Cursor,
  • experience with Copilot Workspace,
  • experience leveraging AI coding agents within software engineering teams,
  • experience working within the insurance or InsurTech domain,
  • experience leading technical direction for engineering teams,
  • experience building internal engineering platforms,
  • experience developing developer productivity tooling,
  • experience defining engineering standards and best practices,
  • experience leading AI-assisted engineering teams,
  • formal enterprise architecture experience, while remaining highly hands-on in software development,
  • interest in emerging AI engineering practices and modern AI-native software development paradigms,

  • 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.


Recruitment Process:

CV review – HR call – InterviewClient Interview – Decision


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