Summary:
- We are seeking a highly skilled and innovative GenAI Specialist to join our team. This role involves leveraging Large Language Models (LLMs) to drive projects and enhance our AI capabilities. The ideal candidate will have extensive experience with various LLMs, tools, and frameworks, and will be responsible for designing, implementing, and monitoring GenAI projects.
Key Responsibilities:
- Usage of Large Language Models in Projects: Utilize models examples: Azure Open AI Model, Gemini 1.5 Model, Claude Model, and Mistral Model to develop and optimize AI solutions. Implement LLM APIs during project work to ensure seamless integration and functionality
- Tools and Technologies:Deploy one of the tools like Google Gemini, Azure OPen AI, AWS Bedrock, AWS Sagemaker, AWS Titan, Azure AutoML / AzureML, and Google Bigquery to support AI development and deployment.
Apply prompt engineering techniques to enhance model performance and accuracy. - End-to-End GenAI Architecture: Design and implement end-to-end GenAI architecture, addressing questions related to architecture design and optimization. Integrate frameworks such as RAG, Langchain, Llama Index, Crew AI, AutoGen, and Agentic AI Framework to support project requirements.
Monitoring and Optimization:
- Develop and implement monitoring frameworks for GenAI projects to ensure model performance and reliability. Manage LLM Ops and Model FinOps to optimize resource usage and cost-efficiency
- LLM Accuracy and Working Experience:Ensure high accuracy of LLMs through rigorous testing and validation. Provide insights and recommendations based on working experience with LLMs to continuously improve AI solutions
- Proven experience with Large Language Models and AI tools.
- Strong understanding of GenAI architecture and frameworks.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.
Preferred Skills:
- Experience with Azure Open AI Model, Gemini 1.5 Model, Claude Model, and Mistral Model.
- Proficiency in using AWS Bedrock, AWS Sagemaker, AWS Titan, Azure AutoML / AzureML, and Google Bigquery.
- Knowledge of prompt engineering techniques and LLM APIs.
- Familiarity with RAG, Langchain, Llama Index, Crew AI, AutoGen, and Agentic AI Framework.
- Strong background in monitoring frameworks and LLM Ops / Model FinOps.