AI Integration Developer
Indexed description
Duration: 3–6 months (extensions possible)
Overview
Seeking an AI Integration Developer to design, build, and maintain AI-assisted workflows supporting scientific data environments. This role focuses on data orchestration, metadata development, and LLM-enabled workflows to improve data accessibility, organization, and analysis.
Key Responsibilities
- Design and implement AI-driven data workflows for scientific datasets
- Analyze data sources and define data location, structure, and ingestion strategies
- Develop and manage metadata frameworks and dataset taxonomy
- Perform data cleansing, normalization, and preparation for storage and sharing
- Package datasets with AI-enabled metadata (HDF5 format) for long-term use
- Build data migration and inventory solutions for retrieval and sharing
- Develop user-friendly interfaces/workflows for research teams
- Support LLM-based data processing and orchestration
- Create and maintain technical documentation, SOPs, and workflow guides
- Ensure solutions follow coding standards, documentation practices, and security requirements
- Strong knowledge of AI/ML concepts and Large Language Models (LLMs)
- Experience designing AI-integrated workflows and prompt engineering
- Familiarity with AI orchestration tools (e.g., Dify or similar)
- Experience with relational databases (MySQL, MariaDB, Oracle)
- Proficiency in Python or scripting languages for automation
- Experience with REST APIs and web services integration
- Working knowledge of Git and version control systems
- Experience with CI/CD pipelines (GitHub, GitLab)
- Strong experience in Linux environments (Debian, RHEL, CLI tools)
- Exposure to GUI development (web-based or Python applications)
- Strong ability to gather requirements and collaborate with technical stakeholders
- Experience working with scientific data systems or research environments
- Exposure to data pipeline architecture and large dataset processing
- Familiarity with data governance, metadata standards, and taxonomy design
- Bachelor’s degree in Computer Science, IT, Systems Engineering, or related field (or equivalent experience)
- 2+ years of experience in software development or system administration
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