Job Overview:

Requirement/Must Have:

- Design and develop efficient maintainable and reusable Python scripts for data extraction, transformation, and loading (ETL) in GenAI applications.
- Demonstrate strong proficiency in the Python programming language.
- Collaborate with cloud platforms such as AWS, Azure, and GCP to build Generative AI (GenAI) applications.
- Develop, implement, and maintain APIs to integrate GenAI models into applications and workflows.
- Conduct research and experiments to explore creative generative AI techniques such as AI agents, hybrid RAG optimization, and workflow orchestration.
- Apply expertise in generative AI concepts including document storage, chunking, vector databases, RAG implementation, and basic fine-tuning methods.

Nice to Have:





- Champion DevOps and MLOps practices focusing on continuous integration, deployment, and AI model monitoring.
- Previous experience leveraging tools like Docker, Kubernetes, and Git to build and manage AI pipelines.
- Experience implementing monitoring and logging solutions to ensure the performance and reliability of AI models.
- Collaboration experience with software engineering and operations teams for seamless AI model integration and deployment.
- Possess familiarity with DevOps and MLOps methodologies emphasizing CICD processes and AI model lifecycle management.

📌 GenAi Developer (Toronto)
🏢 Cynet Systems
📍 Toronto