Role overview

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 innovative 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.

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia—ensuring speed, quality, and consistency in every hire.