| Chennai, Tamil NaduBengaluru, Karnataka
Job Summary
Experience: 10+ years in IT/Software development, with at least 3–5 years specifically delivering enterprise-scale AI/Multi-Agent AI solutions
Programming: Expert-level proficiency in Python with production-grade code quality. Additional proficiency in TypeScript/Node.js is highly regarded
AI/Agentic AI Frameworks & LLM: Deep experience with LLM orchestration (LangChain, LangGraph, LlamaIndex, or AutoGen)
Protocol Mastery : Deep expertise in the Model Context Protocol Specification and its core primitives
Infrastructure & Cloud: Hands-on experience with major cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker and Kubernetes
Data & Vectors : Proficiency with vector databases (Pinecone, Chroma, pgVector ) and knowledge of relational databases or distributed computing frameworks (Spark, Kafka)
API Design : Deep knowledge of REST, GraphQL, and specialized streaming protocols
Soft Skills: Exceptional stakeholder management and communication skills to convey complex AI strategies to non-technical leaders and executives
Key Responsibilities
Architecture Design: Translate business requirements into scalable, secure, and interoperable AI and Generative AI reference architectures
System Design & Integration: Architect multi-system integrations, API orchestrations, and AI-driven workflows (e.g., RAG pipelines, multi-agent systems)
Python Development: Provide architectural leadership and hands-on coding guidance for building production-grade, Python-based AI applications
Maintain a centralized MCP server registry and build internal toolkits to accelerate agent deployment
Skill Requirements
Experience: 10+ years in IT/Software development, with at least 3–5 years specifically delivering enterprise-scale AI/Multi-Agent AI solutions
Programming: Expert-level proficiency in Python with production-grade code quality. Additional proficiency in TypeScript/Node.js is highly regarded
AI/Agentic AI Frameworks & LLM: Deep experience with LLM orchestration (LangChain, LangGraph, LlamaIndex, or AutoGen)
Protocol Mastery : Deep expertise in the Model Context Protocol Specification and its core primitives
Infrastructure & Cloud: Hands-on experience with major cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker and Kubernetes
Data & Vectors : Proficiency with vector databases (Pinecone, Chroma, pgVector ) and knowledge of relational databases or distributed computing frameworks (Spark, Kafka)
API Design : Deep knowledge of REST, GraphQL, and specialized streaming protocols
Soft Skills: Exceptional stakeholder management and communication skills to convey complex AI strategies to non-technical leaders and executives
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