Artificial Intelligence Engineer

Title - AI EngineerType - Contract Location - RemoteRoles and Responsibilities:Design, develop, and deploy AI models, particularly focusing on Large Language Models (LLM) to solve complex problems.Implement Retrieval-Augmented Generation (RAG) frameworks to enhance information retrieval and response accuracy in AI systems.Develop and maintain AI workflows using Langchain to integrate various data sources and AI components effectively.Write clean, efficient, and scalable code primarily in Python to build AI applications and prototypes.Collaborate with cross-functional teams including data scientists, engineers, and product managers to translate business requirements into AI solutions.Continuously research and adopt new AI technologies and methodologies to keep the organization at the forefront of innovation.Optimize AI models for performance, accuracy, and resource efficiency.Monitor and troubleshoot AI systems in production to ensure reliability and robustness. Qualifications:Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related field.2 to 5 years of hands-on experience in AI engineering or related roles.Proven experience working with Large Language Models (LLM) and implementing RAG strategies.Strong proficiency in Python programming and AI/ML libraries.Familiarity with Lang chain or similar frameworks for building AI pipelines.Solid understanding of machine learning concepts, natural language processing, and data structures.Excellent problem-solving skills and the ability to work independently as well as in a team environment.Strong communication skills to articulate complex AI concepts to non-technical stakeholders. Tools and Technologies:Python (primary programming language)Large Language Models (LLM) such as GPT, BERT, or similarRetrieval-Augmented Generation (RAG) frameworks and methodologiesLangchain for AI workflow orchestrationMachine learning libraries and frameworks like TensorFlow, PyTorch, or Hugging Face TransformersVersion control tools such as GitCloud platforms (AWS, Azure, or GCP) for deploying AI models (preferred)

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