Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic AI Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs). Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals. Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities. Model Development and Deployment Design and develop machine learning models and algorithms to address business challenges and improve product features. Deploy machine learning models in production environments to ensure scalability and efficiency. Optimize and refine models based on performance metrics and feedback. Data Management Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation. Implement data augmentation and feature engineering techniques to enhance model performance. Maintain and manage data pipelines to ensure seamless data flow and integration. Python API Development Develop scalable APIs in python (fastApi, Apache, Gunicorn, Uvicorn) for model inferencing Research and Innovation Stay updated with the latest trends and advancements in AI and machine learning technologies. Conduct research to explore new methodologies and techniques that can be applied to current and future projects. Collaborate with cross-functional teams to drive innovation and implement cutting-edge solutions. Collaboration and Communication Work closely with software engineers, data scientists, and product managers to align AI / ML initiatives with business goals. Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner. Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.s.

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