Experience: 12+ Years
We are seeking an experienced AI Architect to lead the design and implementation of advanced agent-to-agent (A2A) interaction systems. This role will focus on architecting and delivering autonomous, collaborative AI agents using the MCP (Agent-to-Agent) framework. The ideal candidate will have deep expertise in multi-agent architectures, distributed AI systems, and enterprise integrations. Experience with ServiceNow is a plus but not mandatory.
Key Responsibilities
• Architect and implement agent-to-agent interaction capabilities, enabling autonomous collaboration, coordination, and task delegation among AI agents.
• Design and deliver solutions using the MCP (Agent-to-Agent) framework, ensuring scalability, reliability, and extensibility.
• Define architectural patterns for multi-agent orchestration, communication protocols, shared memory, and state management.
• Lead technical design sessions and provide architectural governance for agent-based AI solutions.
• Integrate AI agents with enterprise systems, APIs, and workflows (e.g., ITSM, ERP, CRM platforms).
• Ensure observability, security, and governance across agent interactions, including logging, monitoring, and policy enforcement.
• Collaborate with engineering, data science, and platform teams to translate business requirements into agent-based architectures.
Required Qualifications
• 6+ years of experience in AI architecture.
• Hands-on experience building agent-to-agent (A2A) interaction systems in real-world or production environments.
• Strong expertise with the MCP (Agent-to-Agent) framework and multi-agent design patterns.
• Deep understanding of LLM-based systems, autonomous agents, and tool-augmented reasoning.
• Proficiency in Python and/or JavaScript.
• Solid experience with distributed systems, APIs, event-driven architectures, and cloud platforms.
• Strong architectural, problem-solving, and communication skills.
Preferred Qualifications
• Experience integrating AI agents with ServiceNow (ITSM, ITOM, or custom workflows).
• Experience with enterprise automation platforms and workflow engines.
• Knowledge of AI governance, security, and responsible AI practices.
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