
Lead AI Engineer – Chatbot
2 days ago
We are seeking an experienced and hands-on Chatbot Development Lead to spearhead the design, development, and deployment of advanced AI chatbot solutions. The ideal candidate will be proficient in natural language processing (NLP), text-to-SQL conversion, and leading full-stack development using Streamlit and ReactJS. The role requires strong expertise in AWS Bedrock, ECS deployment, and secure authentication integration using AWS SSO. This is a leadership position that involves both technical execution and mentoring a cross-functional development team.
Key Responsibilities:- 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.
- 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.
- 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.
- Opportunity to work with cutting-edge LLM and AI technologies.
- Leadership role with autonomy and decision-making power.
- Competitive compensation and benefits.
- Exposure to full cloud-native deployment lifecycle on AWS.
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