Developed an AI-powered marketing chatbot assistant, integrating OpenAI GPT models and custom

prompt pipelines to generate context-aware responses, summarize customer queries, and deliver

personalized content recommendations.

• Designed backend services in FastAPI/Django to handle chatbot conversation flows, message embeddings,

and semantic search, improving response relevance by 28% through vector-based retrieval (FAISS).

• Developed ML-powered features such as intent classification, sentiment scoring, and content-quality

evaluation using transformer models and OpenAI embeddings.

• Created scalable ETL pipelines to ingest and aggregate chat logs, fine-tune datasets, and marketing

performance data in PostgreSQL and AWS S3 for downstream analytics.

• Deployed dashboard and analytics services to AWS using Docker containers and implemented CI/CD

pipelines to support multi-environment releases.

• Collaborated closely with product managers, data scientists, and marketing strategists to translate AI

insights into user-facing features, improving customer engagement and reducing manual content

generation workload.