AI Developer

Quick Facts

• Role: AI Developer (GenAI/LLM, RAG, MLOps/LLMOps)
• Focus: Claims-handling support ecosystem + advanced AI/GenAI

Description

Join a digital transformation program to build a modern ecosystem supporting claims handling and advanced AI/GenAI capabilities. You will design, tune, and deploy GenAI/LLM and AI-agent solutions on Azure, including RAG and evaluation-driven optimization. The role also covers integration of AI with business systems and supporting AI Governance/AI Act compliance.

Responsibilities

• Design, tune, and implement advanced AI/ML and GenAI solutions using Azure AI Foundry and Azure Machine Learning
• Build and optimize MLOps/LLMOps pipelines with Azure ML, MLflow, Docker, Kubernetes/AKS, and CI/CD
• Integrate AI solutions into a new ecosystem of systems
• Implement advanced RAG using Azure AI Search and work with latest LLMs in Azure OpenAI
• Contribute to AI Governance and AI Act compliance (technical documentation and model monitoring)
• Collaborate with business and IT teams, present results, and support adoption and rollout of AI solutions

Requirements

• Minimum 3 years of experience as an AI Engineer, AI Developer, or related role
• At least 1 year of experience with production deployments
• Practical experience in GenAI/LLM and AI agent solution design and deployment
• Very strong Python
• Experience building/maintaining MLOps/LLMOps using Azure Machine Learning, MLflow, Docker, Kubernetes, and CI/CD
• Experience with LLM models, RAG, and Prompt Engineering
• Strong knowledge of Microsoft Azure AI services used for GenAI/AI
• Experience integrating AI solutions with business systems using REST API and asynchronous communication/integration platforms
• Experience working with source code management tools (Git, Azure DevOps, or GitHub)
• Ability to assess quality of AI-generated responses and use evaluations to optimize

Benefits

• B2B contract
• 3 days per week working from the client office in Warsaw (near M2, close to the city center)
• Professional recruitment process with feedback regardless of outcome