Agentic AI Orchestrator

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