AI Engineer

2 weeks ago

New Delhi, India Vivanet Full time

AI EngineerExperience: 2–6 yearsLocation: Pune/Hyderabad/Bengaluru - Work from officeEmployment Type: C2H/Full-timeAbout VivanetAt Vivanet, we’re building intelligent, reliable, and future-ready technology solutions that help businesses stay ahead in an AI-driven world.With over two decades of experience in technology, leadership, and innovation, we’re now focused on harnessing the power of Agentic AI to solve real-world challenges — blending human insight with intelligent automation.We’re looking for an AI Engineer who’s excited by the idea of turning AI research and frameworks into scalable, production-grade systems that make a measurable difference.About the RoleAs an AI Engineer at Vivanet, you’ll be part of a high-impact team working on advanced Agentic AI systems and AI-powered products. You’ll design and implement reasoning-driven, context-aware AI workflows using modern frameworks like LangChain and LangGraph, and help us extend our ecosystem with MCP (Model Context Protocol) integrations.This is a hands-on role where you’ll blend your skills in AI engineering, software design, and problem solving to create solutions that are intelligent, reliable, and enterprise-ready.Key Responsibilities- Design and develop Agentic AI systems capable of reasoning, planning, and executing complex tasks autonomously. - Build and optimize AI pipelines using LangChain, LangGraph, and related frameworks for context management, memory, and orchestration. - Work with MCP (Model Context Protocol) to establish structured context sharing and inter-agent communication. - Integrate AI components into scalable APIs and backend systems for enterprise deployment. - Collaborate with product and engineering teams to design end-to-end intelligent workflows aligned with business objectives. - Evaluate and integrate new frameworks, models, and tools to enhance solution performance and adaptability.Required Skills- Strong proficiency in Python and hands-on experience with AI frameworks like LangChain, LangGraph, LlamaIndex, PyTorch, Transformers, or FastAPI. - Working knowledge of Agentic AI architectures, including multi-agent collaboration, reasoning, and tool-use systems. - Familiarity with MCP (Model Context Protocol) and structured context handling. - Experience in RAG (Retrieval-Augmented Generation) pipelines and vector databases (Pinecone, FAISS, Milvus). - Solid grounding in data structures, algorithms, and software design principles. - Strong debugging, performance optimization, and communication skills.Desired / Nice-to-Have- Experience with Java, especially for backend or microservice integration. - Exposure to knowledge graphs, function calling, and multi-agent orchestration. - Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). - Understanding of DevOps – CI/CD for models, deployment automation, and monitoring.

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