AI Ecosystem & Intelligence Platform Architect
Summary
Designs and builds enterprise-scale AI architectures using LLMs, multi-agent systems, and RAG workflows, integrating vector databases and ensuring governance and performance across cloud environments.
**Key Responsibilities**
- Design and build multi-model AI architectures that leverage Large Language Models (LLMs) for enterprise-scale applications
- Orchestrate complex AI workflows across multiple models, ensuring seamless integration and optimal performance
- Develop and maintain knowledge fabric systems and integrate enterprise data stores with AI platforms
- Implement Model Context Protocol (MCP) standards and build comprehensive tool ecosystems for AI agents
- Design and deploy agentic systems with Multi-agent orchestration capabilities for autonomous task execution
- Ensure platform reliability, determinism, and cost optimization across all AI infrastructure components
- Establish and enforce governance frameworks for AI systems, including monitoring, compliance, and quality assurance
- Integrate Vector databases and implement Retrieval-Augmented Generation (RAG) architectures for enhanced AI capabilities
- Collaborate with cross-functional teams to translate business requirements into scalable AI solutions
- Optimize system performance and scalability across distributed cloud environments
B.E / M.E, B,Tech / M.Tech
8 to 12 Years