Agentic AI Orchestrator

Agentic AI Orchestrator

Miami, Florida Job Title:

Agentic AI Orchestrator Job Title:

Agentic AI Orchestrator

Location:

Remote

Salary:

 Full-Time | $140K-$170K Base + Performance Bonus (Total Comp Potential ~$220K) Reports to: CEO Job #: 7372 About the role This is one of the newest and fastest-growing roles in AI. As an Agentic AI Orchestrator, you design and operate systems where multiple specialized AI agents collaborate to complete complex, multi-step workflows — autonomously and reliably in production. You're not building chatbots. You're architecting coordination layers: defining how agents communicate, delegate, fail gracefully, and recover — at scale. This role sits at the intersection of systems engineering, AI architecture, and product thinking. What you'll architect Agent coordination Define communication protocols between specialized agents Task routing Distribute subtasks to the right agent at the right time State & memory Manage shared context, working memory, and checkpointing Failure handling Design fallback logic, retries, and graceful degradation What you'll own Design end-to-end multi-agent architectures — from orchestration topology to inter-agent communication schemas Build and maintain the orchestration layer using frameworks such as LangGraph, AutoGen, CrewAI, or custom-built systems Define agent roles, capabilities, and boundaries — research agents, coding agents, data agents, tool-use agents, and critic/evaluator agents Implement robust task decomposition: break complex goals into agent-executable subtasks with clear success criteria Manage shared memory, vector stores, and context windows across agent interactions to prevent hallucination and state drift Design tool-use layers: connect agents to APIs, databases, code interpreters, web search, and internal systems Build observability into multi-agent pipelines — trace agent calls, log decisions, monitor token costs, and detect failure patterns Establish evaluation frameworks for agentic workflows: correctness, latency, cost per task, and task completion rates Collaborate with ML Engineers and product teams to translate business workflows into agent-executable pipelines Maintain security and permission boundaries — agents must not exceed their defined scope or access unauthorized systems Required 3+ years software or AI engineering, systems in production Python (expert) — async patterns, concurrency

LLM APIs:

OpenAI, Anthropic, or Gemini (tool use, function calling) Agent frameworks: LangGraph, AutoGen, or CrewAI RAG pipelines and vector database integration REST / GraphQL API design and consumption Prompt engineering for agent personas, instructions, and constraints Strong debugging instinct — agents fail in non-obvious ways Strong plus Custom orchestration without a framework (raw LLM + state machine) Multi-modal agents: vision, code execution, document processing LangSmith, Arize, or custom eval tooling for agents Experience with OpenAI Assistants API or Anthropic tool use Fine-tuned models used as specialized sub-agents Workflow automation (n8n, Zapier, or custom task queues) Security design for agentic systems (scope, sandboxing, guardrails) Experience in B2B SaaS, recruiting tech, or operations automation Tech stack PythonLangGraphAutoGenCrewAIOpenAI / Anthropic APIsPinecone / pgvectorRedisFastAPI