Lead Assistant Manager

Job Summary

Key Responsibilities

• Design and develop scalable Agentic AI and Generative AI-based applications and pipelines.
• Implement Retrieval-Augmented Generation (RAG) architectures to enhance LLM performance with dynamic knowledge integration.
• Fine-tune and deploy NLP and deep learning models to solve real-world business problems.
• Build autonomous agents that can execute goal-oriented tasks independently.
• Develop robust APIs using FastAPI and integrate with Langchain workflows.
• Work in a Linux environment for model development and production deployment.
• Collaborate with cross-functional teams to drive ML product delivery end-to-end.
• Write optimized code in Python, manage datasets and queries using SQL.
• Keep pace with rapid advancements in the AI/ML space and propose innovations.
  

Required Skills & Qualifications

• Strong expertise in Agentic AI, Generative AI, RAG, NLP, and Deep Learning.
• Solid programming skills in Python and SQL.
• Proficient in Langchain, FastAPI, and working in Linux environments.
• Experience in building and scaling ML pipelines, and deploying models into production.
• Knowledge of vector databases, prompt engineering, and LLM orchestration is a plus.
• Strong analytical and problem-solving skills, with the ability to work in Agile teams.