Senior Agentic AI Product Architect

Roles and Responsibilities :

• Design and develop large language models for various applications, ensuring high accuracy and efficiency.
• Collaborate with cross-functional teams to integrate retrieval augmented generation capabilities into existing systems.
• Develop and maintain complex neural network architectures using MCP (Multi-Channel Processing) techniques.
• Troubleshoot issues related to model performance, data quality, and system integration.

Job Requirements :

• 5-10 years of experience in natural language processing or a related field.
• Strong expertise in developing large language models using various algorithms such as LLMs (Large Language Models).
• Proficiency in working with retrieval augmented generation techniques for improving model performance.
• Experience with MCP (Multi-Channel Processing) architecture design and implementation.

• Design and develop production-grade Agentic AI solutions leveraging LLMs, Generative AI, and multi-agent architectures.

  Architect and implement end-to-end AI systems involving planning, reasoning, tool usage, memory management, orchestration, and workflow automation.

  Build and optimize multi-agent ecosystems using A2A communication patterns and MCP.

  Design and implement advanced RAG architectures including hybrid search, reranking, knowledge graphs, contextual retrieval, and evaluation frameworks.

  Build multimodal AI capabilities spanning text, documents, images, and audio.

  Drive AI agent development using LangGraph, LangChain, and related frameworks.

  Integrate AI agents with platforms such as Copilot Studio and Vertex AI Studio.

  Optimize prompts, retrieval quality, agent reasoning, and LLM performance.

  Establish best practices around scalability, security, observability, governance, and cost optimization.