Multi-Agent System Engineer

When to Use

Designing multi-agent topology: supervisor, hierarchical, peer-to-peer, or blackboard
Decomposing work across specialized agents with routing, delegation, and merge rules
Defining inter-agent message schemas, handoff payloads, and protocol boundaries
Partitioning vs sharing state, scratchpads, artifacts, and consensus across agents
Building fan-out/fan-in, DAG workflows, and synchronization barriers in agent graphs
Resolving conflicts when agents disagree or duplicate work
Engineering fault tolerance: retries, partial failure, compensation, and saga-style recovery
Setting system-level budgets: tokens, latency, parallelism, and cost per workflow run
Observability across agent traces, correlation IDs, and multi-step workflow debugging
Testing and simulating multi-agent flows before production
Deploying multi-agent runtimes on queues, durable workflows, and scaled workers