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Prague, Czech RepublicHybrid

Data Orchestration & AI Engineer

About

The Senior Data Orchestration & AI Engineer will design, develop, and support an AI-enabled Data Orchestration Platform. This role focuses on workflow automation, intelligent recommendations, data movement, monitoring, and auditability across cloud and on-premises environments.

Responsibilities

  • Develop and maintain Python-based services and APIs for the Data Orchestration Platform.
  • Integrate AI/LLM capabilities for request analysis, recommendations, and workflow automation.
  • Build and support data orchestration workflows across cloud and on-premises environments.
  • Integrate data movement solutions and enterprise platforms using secure APIs and automation.
  • Implement monitoring, logging, security controls, and audit mechanisms.
  • Create automated tests, deployment pipelines, technical documentation, and operational runbooks.
  • Participate in end-to-end SDLC activities, including design, development, testing, deployment, and support.

Requirements

  • 5+ years of experience in Software Engineering, Data Engineering, Cloud Engineering, or related fields.
  • Strong hands-on experience with Python development.
  • Experience integrating AI/LLM capabilities into enterprise applications.
  • Good knowledge of REST APIs, SQL, Git, automated testing, and secure application development.
  • Familiarity with RAG, Agentic AI, Prompt Engineering, Structured LLM Outputs, and Human-in-the-Loop workflows.
  • Experience working with AWS and hybrid cloud/on-premises environments.
  • Knowledge of data movement technologies and protocols such as S3, SMB, NFS, and APIs.
  • Understanding of CI/CD, Infrastructure Automation, Monitoring, Security, and Auditability.
  • Experience with enterprise tools such as Jira and ServiceNow is preferred.
  • Experience in regulated, scientific, or laboratory environments is an advantage.
  • Bachelor's degree in Computer Science, Engineering, or a related field preferred. Equivalent experience will also be considered.

Preferred qualifications

AWS services such as S3, IAM, CloudWatch, EFS, and DataSync.

Experience with SMB/NFS file systems and data transfer technologies.

Knowledge of RAG, Agentic AI, Vector Search, Semantic Search, and AI Evaluation.

Experience with Robot Framework or similar automation testing tools.

Exposure to Terraform, Ansible, Docker, and Kubernetes.

Experience working with scientific/laboratory data, regulated environments, data integrity, or GxP-related processes.

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