Machine Learning & NLP Engineer (Chatbots & Agentic AI)

Job Context: Intellica Bangladesh Ltd. is looking for two passionate and skilled Machine Learning & NLP Engineers (Chatbots & Agentic AI) to join our innovation-driven team. The selected candidates will take part in designing and deploying intelligent, explainable NLP systems, including chatbots, retrieval-augmented generation (RAG) pipelines, and autonomous multi-agent frameworks integrated with enterprise platforms such as HR, CRM, and ERP.

This position requires end-to-end ownership of production-grade AI — from data ingestion and model training to deployment, monitoring, and optimization. You will collaborate with cross-functional teams to develop scalable, high-performance solutions that enhance automation, analytics, and decision-making through machine learning, natural language processing, and data analytics.

Job Responsibilities

• Design, train, fine-tune, and evaluate Machine Learning and NLP models for chatbot, CV screening, and predictive analytics applications.
• Develop and deploy conversational AI and multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, and AutoGen, incorporating memory, planning, and safe execution.
• Implement Retrieval-Augmented Generation (RAG) architectures, including data loaders, text chunking, embeddings, and vector databases (Pinecone, Weaviate, FAISS).
• Build and maintain microservices using FastAPI or Flask, containerize with Docker, and implement CI/CD pipelines for production automation.
• Ingest, clean, and analyze large datasets using MySQL, Pandas, and NumPy to extract actionable insights.
• Integrate AI components into enterprise systems (HR, CRM, ERP, support platforms) via REST or GraphQL APIs, in collaboration with backend and DevOps teams.
• Establish LLM operations and safety mechanisms, including model drift detection, guardrails, and human-in-the-loop validation processes.
• Implement explainability and governance frameworks using SHAP, LIME, and attention visualization, and maintain model documentation and data sheets.
• Deploy and manage AI applications on AWS, Azure, or GCP, ensuring observability through CloudWatch, ELK, or Grafana while maintaining cost and security best practices.
• Research, experiment, and contribute to internal templates, libraries, and best practices; participate in hackathons and innovation sprints.