AI Engineer

Experience: 6 Years +

**Key Responsibilities**

• Design and develop a production-grade Multi Agent Runtime that manages agent lifecycle, state persistence, audit logging, and orchestration of specialized diagnostic agents
• Build and optimize the Principal Agent that dynamically schedules tasks and aggregates results from downstream agents (Performance, Topology, Alarm, Ticket, CX, and Event Scout) using the Model Context Protocol (MCP)
• Implement the RCA Inspector reasoning engine that analyzes multi-source incident context against structural playbooks and historical data to produce ranked, explainable root cause hypotheses
• Maintain stream-to-stream API contracts and integrations with neighboring systems, including Data Stream (Pub/Sub anomaly consumption), Knowledge Stream (semantic graph queries), and Experience Stream (WebSocket/SSE operator dashboards)
• Build secure, human-in-the-loop integrations for the Remediation Agent to interface with backend APIs, enabling controlled actions such as traffic reroutes, ticket creation, and partner notifications under strict approval gates
• Ensure all agent decisions, intermediate steps, and reasoning are logged and reconstructable for full auditability and explainability