AI Engineer 100% Remote/up to 430 Euro/MD
nemensis
Contact person: Jan Sebesta
prague, Czech Republic
ITApplication Programming Interfaces (APIs)Microsoft AzurePython (Programming Language)Windows APIArtificial Intelligence Markup Language (AIML)
Description
Project description:
Job responsibilities:
Must have skill:
Nice to have skill:
Our client in the energy industry is looking for two AI Developers to support an intelligent automation & digitalization program. The engagement covers the end-to-end lifecycle: requirements analysis, solution design, implementation, go-live, and post-deployment DevOps operations, maintenance, and continuous improvement.
The technical scope focuses on Python backend development (e.g., FastAPI), AI orchestration frameworks (LangChain, LangGraph), LLM integration, and low-code AI development with Microsoft Power Platform / Copilot Studio. Solutions are built in a Microsoft Azure / Power Platform environment, using services such as Azure OpenAI, Azure Document Intelligence, Azure Blob Storage, and Azure Storage Queues, with potential integration into enterprise landscapes (e.g., SAP).
Start: 15.05.2026
Duration: 6 months (option to extend)
Workload: Full-time
Location: Remote
Language: English - C1
- Design and develop AI Agents using Azure AI Foundry
- Build and enhance Copilot Studio Agents within Microsoft Power Platform
- Implement LLM-based information extraction pipelines (e.g., document processing / data extraction)
- Develop and maintain APIs and system integrations (backend services with Python/FastAPI)
- Implement event-driven / queue-based processing patterns
- Drive end-to-end integrations across enterprise systems (incl. potential SAP interfaces)
- Consult on deployment, monitoring, operations, and continuous optimization of AI solutions
- Python (backend engineering)
- FastAPI
- Azure (building solutions in an Azure environment)
- Azure OpenAI
- Azure AI Foundry (AI agent development)
- Microsoft Power Platform — especially Copilot Studio
- LangChain
- LangGraph
- Strong experience with LLM integration and production-grade AI solution development
- Azure Storage Queues (queue-based processing)
- Azure Blob Storage
- Azure Document Intelligence
- Event-driven architecture experience
- Enterprise integration experience (e.g., SAP landscapes)
- DevOps/operations experience for monitoring, maintenance, and continuous improvement of AI systems
Last edited: 05/07/2026