Agentic AI Data Warehouse Architect

Quick Facts

• Long-term cooperation
• Hybrid work model: 3 days/week in the Wrocław office, 2 days remote
• Benefits include private medical care and a Multisport card

Description

As an Agentic AI Data Warehouse Architect, you will design and develop Agentic AI solutions based on large language models (LLMs), including RAG, hybrid search, and multimodal AI, and integrate them with existing enterprise data platforms.

You will own the data architecture (Data Warehouse, Lakehouse, Medallion Architecture) and build the integration and data processing patterns required for scalable AI applications.

You will deploy and optimize AI solutions on Microsoft Azure using Azure AI Services and Azure OpenAI, focusing on response quality, performance, and cost.

Role & Responsibilities

• Design and evolve Agentic AI architectures using LLMs
• Build AI solutions in Python with LangGraph and LangChain
• Design data architecture: Data Warehouse, Lakehouse, Medallion Architecture
• Model data using conceptual modeling and Kimball methodology
• Design and implement data integration and data processing patterns
• Develop data engineering solutions with Azure and Databricks
• Develop Data Products
• Build RAG, Hybrid Search, and Multimodal AI solutions
• Design Context Engineering, Prompt Engineering, and Memory Engineering for LLM applications
• Implement AI solutions using Azure AI Services and Azure OpenAI
• Optimize LLMs for performance, answer quality, and cost
• Design scalable AI architectures and integrate them with existing data platforms

Requirements

• Experience designing AI architectures, especially Agentic AI and LLM-based applications
• Strong experience in Data Warehouse and Data Architecture (mandatory)
• Strong Python experience for AI solutions
• Practical experience with LangGraph and LangChain
• Experience designing and implementing Agentic AI systems
• Advanced data modeling: Conceptual Data Modeling and Dimensional Data Modeling (Kimball)
• Experience designing Lakehouse and Medallion Architecture
• Knowledge of data integration patterns
• Practical experience with data processing using Azure and Databricks
• Experience designing and developing Data Products
• Knowledge of Context Engineering, Prompt Engineering, and Memory Engineering
• Experience designing and deploying RAG solutions
• Knowledge of Hybrid Search and Multimodal AI architectures
• Practical knowledge of Azure AI Services and Azure OpenAI
• Experience deploying AI solutions in cloud environments
• Knowledge of LLM optimization and evaluation, including cost optimization
• Ability to connect AI solutions with existing data platforms and architecture
• English level B2–C1
• Hybrid availability: 3 days/week in the Wrocław office, 2 days remote (non-negotiable)

Benefits

• 200–230 PLN net/hour + VAT
• Support in setting up and running a business (including for candidates without prior experience)
• Efficient recruitment process: two technical interviews with managers (online, max 1 hour each)
• Modern hardware provided with required software and configuration
• Private medical care and Multisport card