Job Description

Roles & Responsibilities

• Designing and building Generative AI applications using Large Language Models (LLMs) · Developing Agentic AI solutions, including autonomous agents, multi-agent orchestration, and workflow-driven decision systems · Building solutions using frameworks such as LangChain, LangGraph or similar agent frameworks · Implementing RAG architecture with vector databases · Knowledge of embeddings, vector DBs, and model evaluation. · Implement various Context Engineering strategies to reduce Token Utilization & Latency. · Prompt engineering, tool calling, memory management, and agent orchestration · Integrating AI services with enterprise APIs, middle ware, and backend systems · Evaluated & Improvise AI Agent Performance using several metrics · Deploying scalable AI solutions on Azure / AWS cloud platforms

Desired Candidate Profile

• Possesses a Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, providing a strong theoretical foundation.

• Demonstrates 8+ years of hands-on experience in developing and deploying AI agents, showcasing practical expertise.

• Holds a strong command of Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch), demonstrating proficiency in implementation.

• Exhibits a deep understanding of agent architectures, including multi-agent systems, and their applications.