Lead AI Engineer Chatbot & NLP

As an experienced and hands-on Chatbot Development Lead, you will spearhead the design, development, and deployment of advanced AI chatbot solutions. Your proficiency in natural language processing (NLP), text-to-SQL conversion, and leading full-stack development using Streamlit and ReactJS will be key in this role. You will need strong expertise in AWS Bedrock, ECS deployment, and secure authentication integration using AWS SSO. This leadership position involves both technical execution and mentoring a cross-functional development team. - Lead end-to-end development of AI-powered chatbot solutions with Text-to-SQL capabilities. - Architect and implement intuitive custom UI using Streamlit for internal tools and ReactJS for production-facing applications. - Build and optimize NLP pipelines integrated with AWS Bedrock foundation models. - Manage containerized deployment using AWS ECS, including task definitions, load balancers, and autoscaling. - Integrate enterprise-grade security via AWS Single Sign-On (SSO). - Drive sprint planning, code reviews, and delivery milestones for the chatbot team. - Collaborate with product managers, data scientists, and DevOps engineers to ensure seamless delivery. - Stay updated on the latest in AI, LLM, and cloud technologies to drive innovation. **Required Skills:** - Strong hands-on experience in Python, Streamlit, ReactJS, and full-stack development. - Expertise in Text-to-SQL modeling, fine-tuning LLMs, and natural language interfaces. - Proficiency with AWS Bedrock and deploying generative AI applications on AWS. - Experience with Docker and ECS (Elastic Container Service) for scalable deployment. - Knowledge of IAM roles, security best practices, and AWS SSO integration. - Proven ability to lead and mentor a team, manage priorities, and deliver high-quality solutions. - Familiarity with CI/CD pipelines, logging/monitoring, and Git-based workflows. **Preferred Qualifications:** - Experience with vector databases and semantic search (e.g., OpenSearch, Pinecone). - Prior experience building internal developer tools or enterprise chat interfaces. - Understanding of RAG (Retrieval-Augmented Generation) and LangChain or similar frameworks. - AWS Certifications (e.g., AWS Certified Solutions Architect, Machine Learning Specialty) is a plus. In this role, you will have the opportunity to work with cutting-edge LLM and AI technologies, hold a leadership position with autonomy and decision-making power, receive competitive compensation and benefits, and gain exposure to the full cloud-native deployment lifecycle on AWS.,