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# AI Architect - Hybrid 3 Days in office-San Jose , CA

- **Company:** InfiCare Inc
- **Location:** San Jose, CA, United States
- **Experience:** Experienced
- **Contract:** Contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Architectural Patterns, Microsoft Azure, Programming Tools, Python (Programming Language), Software Architecture, TypeScript, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Agentic-AI, Containerization, AI Platforms, Kubernetes, Low Latency, Production Code, CrewAI, AutoGen, Machine Learning Operations, Software Coding, Model Context Protocol, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.dice.com/job-detail/5e498525-9421-4e71-bb38-023b103fa255

## About the Role

* Experience: 10+ years of software architecture experience, with at least 3+ years of dedicated, hands-on experience building and deploying production-grade LLM applications and AI systems.
 * AI & Agentic Expertise: Deep understanding of multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI), prompt engineering, RAG pipelines, and vector databases.
 * Protocol & API Mastery: Proven experience with Model Context Protocol (MCP) or designing similar context-sharing and tool-calling protocols for GenAI.
 * Technical Stack: Proficiency in Python, TypeScript, or Go, along with cloud native technologies (AWS/Google Cloud Platform/Azure, Kubernetes, Docker) and modern AI SDKs.
 * Communication: Outstanding verbal and written communication skills, with a proven ability to lead technical discussions and author comprehensive architecture RFCs.

## Description

We are seeking a highly skilled, hands-on Lead AI Systems Architect to design, build, and scale our next-generation AI ecosystem. In this role, you will lead the architecture and implementation of Agent-to-Agent frameworks, Model Context Protocol (MCP) integrations, and our proprietary AI development platform.

This is not a purely theoretical role. You must be deeply technical, actively writing code, and capable of translating complex AI research into robust, production-grade software. As a key bridge between engineering teams and stakeholders, you must also possess exceptional communication skills to articulate technical vision and drive cross-functional alignment.

Core Responsibilities:

 * Agent-to-Agent Architecture: Design and implement multi-agent orchestration frameworks, focusing on autonomous negotiation, task delegation, state management, and secure inter-agent communication.
 * MCP Integration: Architect and build scalable Model Context Protocol (MCP) servers and clients to securely connect LLMs to data sources, development tools, and enterprise environments.
 * AI Platform Development: Drive the architectural vision for our internal AI development platform, ensuring high throughput, low latency, and seamless developer workflows for training, testing, and deploying models.
 * Hands-on Engineering: Write high-quality, production-ready code, build prototypes, and establish engineering best practices for AI application development.
 * Technical Leadership & Communication: Standardize architectural patterns across the organization. Mentor junior engineers and explain complex technical concepts to non-technical stakeholders clearly and effectively.