Lead AI Engineer – Chatbot & NLP

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.

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.

What We Offer :

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.