LangGraph StateGraph & Routing
Stateful cyclical and acyclic agent graphs, supervisor-worker coordination, and checkpointing for full workflow resumability after third-party API interruptions.
Agentic AI Workflows & Runtimes
I architect stateful, error-isolated multi-agent workflows using LangGraph, structured memory contracts, deterministic guardrails, and asynchronous task execution that survive model rate-limits, context bloat, and hallucinations.
Solutions Architect on the Wellows LLM search visibility platform (KIVA, OPTA, Citation Intelligence) with sub-200ms vector retrieval and 80% manual workflow reduction.
Agent Engineering Deliverables
Every agentic system I design has explicit memory boundaries, schema validation, rate-limit backpressure, and human-in-the-loop gates.
Stateful cyclical and acyclic agent graphs, supervisor-worker coordination, and checkpointing for full workflow resumability after third-party API interruptions.
Input sanitization, strict Pydantic output schema validation, prompt injection defense, and automated evaluation suites testing against hallucination drift.
Hybrid dense-sparse retrieval, semantic re-ranking, chunk-size optimization, and asynchronous vector indexing pipelines accessible across all agent nodes.
Decoupling agent tool execution behind Celery/SQS queues, exponential retries with jitter, and human escalation gates before high-risk external actions.
Architecture Engagement Path
Map domain actions into isolated agent responsibilities with unambiguous input/output JSON contracts.
Build deterministic routing, checkpointed persistence, and thread-scoped context windows to prevent token bloat.
Connect hybrid vector stores, configure API rate-limit circuit breakers, and enforce Pydantic validation on all tool outputs.
Set up tracing (OpenTelemetry/LangSmith), cost-tracking monitors, latency alerts, and complete operational runbooks.
Start with clarity
Let’s map out your agent state graph, failure boundaries, and execution roadmap in a 30-minute architecture review.