Senior AI Engineer

Join a global life science and healthcare company as a Senior Python Engineer in the Data & Analytics AI Engineering team. The role involves turning AI ideas and prototypes into robust, production-ready solutions that run at enterprise scale. Work is strongly hands-on, focused on software engineering, AI system design, and production deployments. The position includes opportunity to join the internal team of the customer and work from office in Warsaw once a week.

• Strong experience as a Software Engineer working with AI-related solutions.
• Very good knowledge of Python.
• Proven experience in backend and API development.
• Experience designing and working with production system architectures.
• Solid understanding of software engineering practices (code reviews, testing, CI/CD, GitHub or similar).
• Experience deploying and operating applications in production environments.
• Track record of building real AI solutions (not only PoCs or experiments).
• Experience with LLM applications, RAG systems, AI agents / agentic workflows.
• Experience with frameworks such as LangChain, LangGraph or similar.
• Experience evaluating AI system quality and integrating AI models with business systems.
• Experience with AWS or Azure and building/running cloud-native solutions.
• Good understanding of cloud services used to deploy and operate AI applications.
• Ability to independently deliver solutions in a cloud environment.

• Design, build and maintain backend services and APIs for AI-driven applications using Python.
• Develop end-to-end, cloud-native AI solutions from prototype to stable production systems.
• Implement and operate LLM-based applications, RAG systems, AI agents and agentic workflows.
• Integrate AI models and services with existing business systems and data platforms.
• Apply good engineering practices: code reviews, testing, CI/CD, version control and monitoring.
• Collaborate closely with data, product and business stakeholders to solve real business problems with AI.
• Evaluate and improve the quality and reliability of AI systems in production.
• Take strong ownership of assigned topics, drive technical decisions and contribute to the overall AI platform architecture.