AI Engineer

3 weeks ago

Delhi, India Vivanet Full time

AI Engineer Experience: 2–6 years Location: Pune/Hyderabad/Bengaluru - Work from office Employment Type: C2H/Full-time About Vivanet At 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 Role As 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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