AI Engineer

• Build, customize, and deploy AI agents using frameworks like LangChain, AutoGen, CrewAI, and Haystack.
• Enable agent reasoning, planning, and tool-use for complex tasks.
• Implement and optimize RAG pipelines for enterprise-scale knowledge retrieval.
• Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to manage embeddings and context injection.
• Fine-tune retrieval strategies, chunking logic, and metadata tagging for high-quality responses.

Overview

• Industry - IT - Software / Product Development
• Job Role - Technical Lead - Solution Architect - RPA / AI / ML, AI-ML Engineer, AI Engineer
• Employment type - Full Time - Permanent
• Work Mode - Hybrid

Qualifications

• Any Graduate - Any Specialization
• Any Post Graduate - Any Specialization
• Any Doctorate - Any Specialization

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