About the Role
Job Title: AI Architect
Duration: 6months (20hrs/Week)
Location: USA Remote
Description
Job Summary
We are seeking an experienced AI Architect to lead the design and implementation of enterprise-grade AI solutions with a strong focus on Agentic AI, Model Context Protocol (MCP), and modern AI integration architectures. The ideal candidate will drive solution shaping, architect scalable AI platforms, design enterprise integrations, and provide hands-on technical leadership to internal engineering teams. This role requires deep expertise in LLM ecosystems, AI orchestration frameworks, cloud-native architectures, and enterprise integration patterns.
Key Responsibilities
Lead solution architecture for enterprise AI, Agentic AI, and GenAI initiatives. Design and implement scalable AI architectures leveraging MCP, AI agents, and enterprise integrations. Shape technical solutions aligned with customer business objectives and enterprise architecture standards. Define architecture patterns, integration strategies, security, and governance for AI solutions. Design integrations between AI platforms and enterprise applications using REST APIs, GraphQL, webhooks, and event-driven architectures. Provide technical leadership and hands-on enablement to internal engineering teams throughout implementation. Collaborate with product, engineering, and business stakeholders to translate requirements into scalable AI architectures. Guide engineering teams on AI best practices, coding standards, deployment patterns, and operational excellence. Review solution designs, perform architecture assessments, and recommend optimization opportunities. Deliver assigned work items in accordance with agreed timelines. Provide accurate effort estimates for assigned work items. Communicate progress, risks, dependencies, and technical challenges proactively. Support proof-of-concepts (POCs), architecture workshops, and customer technical discussions.
Required Technical Skills
AI & Large Language Models
Strong expertise with Model Context Protocol (MCP) including: MCP Servers MCP Clients MCP Connectors Experience with Anthropic Claude models and Claude API. Experience with Google Gemini models. Experience with Vertex AI and Gemini Enterprise. Knowledge of prompt engineering, context management, tool calling, and Retrieval-Augmented Generation (RAG). Agentic AI
Experience designing and implementing Agentic AI systems. Expertise with AI agent frameworks and orchestration platforms such as: LangGraph CrewAI AutoGen Google ADK Semantic Kernel OpenAI Agents SDK (preferred) Cloud & Infrastructure
Strong experience with Google Cloud Platform (Google Cloud Platform). Vertex AI ecosystem. Cloud-native architecture and deployment patterns. Containerization using Docker and Kubernetes is preferred. Programming
Strong proficiency in: Python TypeScript Node.js Enterprise Integration
REST APIs GraphQL Webhooks Enterprise system integrations API design and integration best practices Authentication (OAuth2, JWT, API Keys) DevOps
Git-based source control CI/CD pipelines Infrastructure as Code exposure is a plus
Architecture & Enterprise Experience
Enterprise solution architecture.