Senior GenAI Engineer

Summary

Join Xebia, a global leader in digital solutions, and become an integral part of our team developing and deploying cutting-edge AI applications. This role centers on designing, developing, and implementing AI solutions using Python, focusing on LLMs, vision models, and generative AI technologies. You will build, test, and optimize RAG applications, integrate AI models with Azure AI Studio, and leverage vector databases. Collaboration with senior team members is key to delivering high-quality solutions. The position requires expertise in Azure AI Studio, Azure Blob Storage, Event Hub, and Kafka. Continuous learning and adaptation to emerging AI technologies are essential for success.

Requirements

• Bachelor's degree in computer science, Data Science, Engineering, or a related field
• 4+ years of hands-on experience in AI/ML development, with an emphasis on generative AI and related technologies
• Strong experience with Python, REST APIs, Git
• Proven expertise in developing and deploying LLMs, vision models, vector databases, and RAG applications
• Strong proficiency in Azure AI Studio, Azure Blob Storage, Event Hub, Kafka
• Familiarity with Agentic frameworks and tools like LlamaIndex for advanced AI development
• Ability to thrive in a collaborative team environment while managing multiple tasks effectively
• Good verbal and written communication skills in English (min. B2)
• Work from the European Union region and a work permit are required

Responsibilities

• Designing, developing, and implementing AI solutions using Python, with a focus on LLMs, vision models, and generative AI technologies
• Building, testing, and optimizing RAG applications, leveraging effective prompt engineering techniques to improve model performance
• Integrating AI models with Azure AI Studio, SharePoint, and Azure Blob Storage for efficient deployment and data handling
• Utilizing vector databases and Agentic frameworks (e.g., LlamaIndex) to enhance the functionality and intelligence of AI systems
• Implementing event-driven architectures using tools like Event Hub and Kafka for real-time data processing and scalability
• Collaborating with the AI Lead and team members to troubleshoot issues, test models, and ensure successful deployment
• Writing clean, efficient, and well-documented code adhering to best practices and version control standards
• Staying current with emerging AI tools, frameworks, and technologies to continuously improve development processes and outcomes

Preferred Qualifications

• Previous exposure to cloud fundamentals (Azure preferred) and containerization tools like Docker
• Experience with CI/CD pipelines for AI model deployment
• Understanding RESTful services and API integration