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Open nowPosted 4 hours ago

Data & AI Solutions Engineer

Poland and Middle-Eastern Europe82 open roles

Where
Bulgaria; Poland; Romania
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Your applicationOpen nowData & AI Solutions EngineerPoland and Middle-Eastern Europe · Bulgaria; Poland; Romania
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  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. Poland and Middle-Eastern Europe postings stay open a median of 20 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 4 hours ago

Poland and Middle-Eastern Europe median: 20 days open

The posting

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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, 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.

You will be:

  • developing AI-powered applications and conversational experiences on top of enterprise data,
  • building and prototyping AI agents and copilots for business, commercial, and operational analytics use cases,
  • connecting Large Language Models (LLMs) with structured enterprise data, semantic models, APIs, and existing systems,
  • developing prototypes and solutions using Python, SQL, and APIs, and supporting the transition of successful concepts into production,
  • working with technologies across the Microsoft AI ecosystem, including Azure AI, Microsoft Foundry, Copilot Studio, and Microsoft Fabric,
  • implementing approaches such as RAG, grounding, tool/function calling, and agent orchestration where relevant,
  • evaluating the quality, reliability, security, and accuracy of AI-generated responses,
  • collaborating closely with Data Engineers and BI/Analytics Engineers to leverage governed data products and semantic models,
  • exploring new ways of delivering business insights beyond traditional dashboards, including conversational analytics and AI-generated analytical experiences,
  • keeping up with emerging GenAI technologies and identifying opportunities to apply them to real business use cases.

Your profile:

  • professional experience in Data Engineering, Software Engineering, Cloud Engineering, or a similar technical role,
  • strong Python programming and software engineering fundamentals,
  • strong SQL skills and experience working with enterprise data systems, APIs, and integrations,
  • experience with Azure and/or Microsoft Fabric,
  • practical, hands-on experience with Generative AI and Large Language Models (LLMs),
  • good understanding of data architecture, structured data, and semantic models,
  • experience with Git, DevOps, and scalable software development practices,
  • ability to design and prototype AI-powered solutions and translate business needs into technical approaches,
  • curiosity about emerging AI technologies and willingness to develop further in the GenAI space,
  • good command of English.

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

Nice to have:

  • experience with Azure AI, Microsoft Foundry, Copilot Studio, or Fabric AI capabilities,
  • hands-on experience building AI agents, copilots, or conversational analytics solutions,
  • knowledge of RAG, grounding, tool/function calling, agent orchestration, or Model Context Protocol (MCP),
  • experience working with Power BI semantic models or Databricks,
  • experience with AI-generated analytics, visualizations, or natural-language interfaces for data.

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision

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