AI Architect

As a GenAI Lead, you will be responsible for leveraging your expertise in Generative AI, machine learning, and natural language processing (NLP) to design and implement innovative AI-driven solutions. Your role will involve leading the design and implementation of end-to-end Generative AI solutions, ensuring scalable, robust, and efficient architecture that aligns with business needs. Additionally, you will develop and execute strategies for data collection, cleaning, transformation, and integration for AI model development, applying best practices for data pipeline design and optimization. You will design and implement intelligent AI agents using advanced techniques in NLP and machine learning to improve automation, user interaction, and decision-making processes. Furthermore, you will fine-tune pre-trained models and optimize prompt engineering techniques to drive high-quality, actionable outputs for diverse business use cases. Your responsibilities will also include building, training, and deploying machine learning models, including deep learning models, for complex AI applications across various domains. Moreover, you will lead the provisioning and customization of Large Language Models (LLMs) from major Cloud Service Providers (CSPs) such as Azure, AWS, and Google Cloud, ensuring optimal performance and cost-effectiveness. You will utilize technologies like Langchain, CrewAI, and VectorDB for building, integrating, and scaling NLP solutions, as well as leverage Flask/FastAPI for model deployment and integration. Working with databases (SQL/NoSQL) for data storage, querying, and management to support AI model development and deployment will also be part of your responsibilities. Additionally, you will apply advanced tokenization techniques to preprocess and analyze data for NLP tasks, enhancing model efficiency and performance. You will oversee the deployment of AI models, ensuring smooth integration with production systems, and perform rigorous evaluation of LLMs for accuracy, efficiency, and scalability. Qualifications Required: - Proven experience in understanding GenAI solutions and architectural design for large-scale AI systems. - Expertise in data cleaning, transformation, and data strategy to drive AI and machine learning initiatives. - Strong hands-on experience with AI agents, prompt engineering, and fine-tuning LLMs for business applications. - Proficiency in machine learning models, deep learning techniques, and NLP applications. - Deep knowledge of LLM provisioning from different Cloud Service Providers (CSPs) such as AWS, Azure, Google Cloud. - Experience with Langchain, CrewAI, VectorDB, Flask, FastAPI, and related frameworks for model integration and deployment. - Strong database skills, with proficiency in SQL and experience in working with NoSQL databases.,