Role SummaryWe 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
