Agentic AI Engineer

Responsibilities

• Design, develop, and deploy AI agents to automate complex workflows and business processes
• Build agentic AI applications using LLMs and Generative AI technologies
• Develop multi-agent systems that collaborate to solve complex problems
• Integrate AI agents with external APIs, databases, and enterprise applications
• Implement tool calling, function calling, memory management, and task planning
• Develop Retrieval-Augmented Generation (RAG) pipelines for knowledge-based applications
• Work with frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
• Design prompt engineering strategies to improve agent performance and response quality
• Implement guardrails, validation, monitoring, and error-handling mechanisms
• Evaluate AI agent accuracy, reliability, latency, and cost
• Optimize agent workflows for scalability, efficiency, and security
• Collaborate with cross-functional teams to identify automation opportunities
• Document system architecture, workflows, and technical implementation

Requirements

• Strong programming knowledge of Python
• Understanding of Artificial Intelligence, Machine Learning, and Generative AI
• Knowledge of LLMs, prompt engineering, and transformer-based models
• Familiarity with AI agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
• Understanding of tool calling, function calling, and agent orchestration
• Knowledge of RAG, embeddings, vector databases, and semantic search
• Experience with REST APIs, JSON, and database integration
• Familiarity with vector databases such as FAISS, Chroma, Pinecone, or Weaviate
• Understanding of Git, debugging, and software development best practices
• Strong analytical, problem-solving, and communication skills