Lead AI Engineer

Role Overview: You are an experienced AI Lead Engineer joining a dynamic team focused on driving innovation in AI-driven solutions with a global impact. Your role is tailored for a highly motivated professional with a strong technical background in Python and Java, hands-on expertise in developing Retrieval-Augmented Generation (RAG)-based chatbots, Machine Learning, Deep Learning, and solid cloud deployment experience, preferably on AWS. Key Responsibilities: - Lead the design and development of AI-driven applications, particularly focusing on RAG based chatbot solutions. - Architect robust solutions leveraging Python and Java to ensure scalability, reliability, and maintainability. - Deploy, manage, and scale AI applications using AWS cloud infrastructure, optimizing performance and resource utilization. - Collaborate closely with cross-functional teams to understand requirements, define project scopes, and deliver solutions effectively. - Mentor team members, providing guidance on best practices in software development, AI methodologies, and cloud deployments. - Ensure solutions meet quality standards, including thorough testing, debugging, performance tuning, and documentation. - Continuously research emerging AI technologies and methodologies to incorporate best practices and innovation into our products. Qualifications: - Bachelors or master's degree in computer science, Engineering, Data Science, Mathematics, Statistics, or related fields. - At least 5 years of professional experience in AI/Machine Learning engineering. Additional Details: The company prefers candidates with AWS certifications (e.g., AWS Solutions Architect, AWS Machine Learning Specialty), familiarity with popular AI/ML frameworks and libraries such as Hugging Face Transformers, TensorFlow, PyTorch, LangChain, or similar, experience in Agile development methodologies, excellent communication skills, capable of conveying complex technical concepts clearly and effectively, strong analytical and problem-solving capabilities, with the ability to navigate ambiguous technical challenges. Role Overview: You are an experienced AI Lead Engineer joining a dynamic team focused on driving innovation in AI-driven solutions with a global impact. Your role is tailored for a highly motivated professional with a strong technical background in Python and Java, hands-on expertise in developing Retrieval-Augmented Generation (RAG)-based chatbots, Machine Learning, Deep Learning, and solid cloud deployment experience, preferably on AWS. Key Responsibilities: - Lead the design and development of AI-driven applications, particularly focusing on RAG based chatbot solutions. - Architect robust solutions leveraging Python and Java to ensure scalability, reliability, and maintainability. - Deploy, manage, and scale AI applications using AWS cloud infrastructure, optimizing performance and resource utilization. - Collaborate closely with cross-functional teams to understand requirements, define project scopes, and deliver solutions effectively. - Mentor team members, providing guidance on best practices in software development, AI methodologies, and cloud deployments. - Ensure solutions meet quality standards, including thorough testing, debugging, performance tuning, and documentation. - Continuously research emerging AI technologies and methodologies to incorporate best practices and innovation into our products. Qualifications: - Bachelors or master's degree in computer science, Engineering, Data Science, Mathematics, Statistics, or related fields. - At least 5 years of professional experience in AI/Machine Learning engineering. Additional Details: The company prefers candidates with AWS certifications (e.g., AWS Solutions Architect, AWS Machine Learning Specialty), familiarity with popular AI/ML frameworks and libraries such as Hugging Face Transformers, TensorFlow, PyTorch, LangChain, or similar, experience in Agile development methodologies, excellent communication skills, capable of conveying complex technical concepts clearly and effectively, strong analytical and problem-solving capabilities, with the ability to navigate ambiguous technical challenges.