Agentic Workflow Engineer

Zoho; United States; Remote; USD 120,000 - 170,000; Part time

Job summary

Agentic Workflow is seeking a skilled Multi-Agent Systems Engineer to design, develop, and stabilize autonomous multi-agent networks in a remote offshore setup. The role focuses on production-grade, stateful agents that collaborate, share context, call enterprise APIs, and handle failures gracefully to execute complex business operations independently.

The ideal candidate has 4–8 years in enterprise backend or distributed systems, expertise in Python/TypeScript, async programming, API design,

Qualifications

• 4–8 years of backend/web engineering or distributed systems experience
• 2+ years writing production-grade code for autonomous multi-agent environments
• Proficiency in Python or TypeScript and asynchronous programming
• Understanding of LLM cognitive limits, tool calling, and loop mitigation
• Certification: Professional ML Engineer or cloud ML credential (AWS/GCP/Azure)

Responsibilities

• Design multi-agent orchestration architectures using LangGraph, CrewAI, AutoGen or Semantic Kernel
• Build stateful deterministic and non-deterministic state machines and agent communications
• Implement secure tool execution frameworks to call REST APIs, query SQL and process files
• Configure memory layers: short-term memory and long-term semantic storage
• Establish HITL validation checkpoints for sensitive operations
• Enhance reasoning and planning with ReAct, Plan-and-Solve, self-reflection loops
• Implement observability and tracing with LangSmith, Arize Phoenix or Datadog

Skills

Python

TypeScript

Asyncio

State management

API design

Relational databases

Education

Professional ML Engineer or Specialty ML credential (AWS/GCP/Azure)

Tools

LangGraph

CrewAI

AutoGen

Semantic Kernel

LangSmith

Arize Phoenix

Datadog LLM Observability

Job description

Agentic Workflow / Multi-Agent Systems Engineer

• Employment Type: Contract
  
• Work Mode: Remote
  
• Location: Offshore
  
• Total Experience Required: 4 to 8 years
  
• Relevant Experience Required: 2+ years of dedicated experience developing multi-agent systems, autonomous AI agents, and complex task-planning state machines
  

We are seeking an experienced Agentic Workflow / Multi-Agent Systems Engineer to design, develop, and stabilize autonomous multi-agent networks within our enterprise environment. The ideal candidate will move past single-prompt solutions to build production-grade, stateful multi-agent systems where distinct specialized AI entities collaborate, share context, call enterprise APIs, handle execution failures gracefully, and execute multi-step business operations independently.

Key Responsibilities

• Design and develop multi-agent orchestration architectures using frameworks like LangGraph, CrewAI, AutoGen, or Semantic Kernel.
  
• Build stateful deterministic and non-deterministic state machines, managing conversation loops, task delegation logic, branching paths, and agent-to-agent communication networks.
  
• Implement secure, robust tool execution frameworks, empowering agents to dynamically call enterprise REST APIs, query databases via SQL, and process files within sandboxed runtime execution environments.
  
• Configure sophisticated multi-agent memory layers, setting up short-term transactional memory, long-term semantic vector storage, and cross-agent context sharing protocols.
  
• Establish structured human-in-the-loop (HITL) validation checkpoints, configuring human approval gates for sensitive agentic operations like financial triggers or external data mutations.
  
• Optimize agent reasoning and planning structures, implementing advanced cognitive patterns such as Reason and Act (ReAct), Plan-and-Solve, and self-reflection error-correction loops.
  
• Implement agentic observability and tracing frameworks using platforms like LangSmith , Arize Phoenix , or Datadog LLM Observability to diagnose stuck loops, trace call sequences, and monitor token consumption.
  

Requirements

• 4 to 8 years of core enterprise backend web engineering, asynchronous programming, or distributed systems experience, with 2+ dedicated years actively writing production-level application code for autonomous multi-agent environments.
  
• Strong technical mastery of Python or TypeScript, asynchronous programming (Asyncio), state-management patterns, API integration design, and relational databases.
  
• Deep structural understanding of LLM cognitive limits, tool calling hallucination profiles, infinite loop mitigation strategies, token budget planning, and multi-agent consensus protocols.
  
• Mandatory certification: Professional ML Engineer or Specialty Machine Learning credential from a major cloud vendor (AWS/GCP/Azure).
  

Preferred Qualifications

• Prior experience implementing multi-agent architectures handling multi-modal inputs (e.g., agents processing text, vision, and code generation simultaneously).
  
• Familiarity with deploying containerized multi-agent apps within Kubernetes microservice grids under tight networking isolation guidelines.