AI Solution Architect GenAI Orchestration

Role Summary

We are looking for an experienced AI Solution Architect to design and lead GenAI orchestration platforms with a strong focus on agent-based systems and multi-agent workflows .

The role involves defining end-to-end system architecture, orchestration patterns, and scalable cloud-native deployments on Azure, enabling next-generation AI-driven applications.

Key Responsibilities

• Design and implement agent runtime orchestration using frameworks like LangGraph or similar tools
• Define and standardize orchestration patterns , including intent-based planning, fallback mechanisms, and multi-agent execution flows
• Build stateful agent workflows supporting pause, resume, retry, and execution inspection
• Define and maintain agent integration contracts (e.g., MCP / A2A communication patterns)
• Architect scalable Azure cloud solutions , including compute, storage, IAM, networking, and logging
• Implement observability and monitoring frameworks using tools like Azure Monitor, Application Insights, and Arize
• Provide technical leadership , architecture governance, and best practice guidelines
• Support POC design, prototyping, and execution readiness for AI solutions

Required Skills & Experience

• 7+ years of experience in AI/ML, Solution Architecture, or Platform Engineering
• Strong hands-on experience with Agentic AI and multi-agent systems
• Proficiency in LangChain / LangGraph or similar frameworks
• Deep expertise in cloud-native architecture (preferably Microsoft Azure)
• Experience in AI observability, monitoring, and runtime tracing
• Strong stakeholder management and communication skills

Good to Have

• Experience building GenAI / LLM-based applications
• Exposure to multi-agent orchestration platforms in production environments
• Knowledge of AWS or GCP cloud platforms
• Familiarity with prompt engineering techniques and best practices