AI Agentic Developer

About the job

mroads is looking for an "AI Agentic Developer" for one of the clients in Dallas, TX.

We are seeking an innovative AI Agentic Developer to design, develop, and optimize intelligent AI agents that automate workflows, decision-making, and business processes. The ideal candidate has hands-on experience building AI-driven automation, agent-based systems, and orchestrated flows using LLMs, APIs, and event-driven architectures. This role requires strong problem-solving skills and the ability to translate business processes into autonomous, scalable AI solutions.

Key Responsibilities

· Design and develop AI agents capable of autonomous reasoning, planning, and execution across complex workflows

· Build AI-based automation flows using agentic frameworks, orchestration tools, and workflow engines

· Integrate LLMs (GPT, Claude, Gemini, etc.) into enterprise automation pipelines

· Implement multi-agent systems for task delegation, collaboration, and decision-making

· Develop and maintain event-driven and API-based flows connecting AI agents with enterprise systems

· Optimize prompts, tools, and memory mechanisms for agent performance and reliability

· Implement human-in-the-loop workflows for validation, approvals, and exception handling

· Ensure scalability, security, and observability of AI-driven automation systems

· Collaborate with product, UX, and engineering teams to translate business requirements into AI flows

· Document agent behaviors, workflows, and integration patterns

Required Skills & Qualifications

· 5+ years of experience in AI-based automation, intelligent workflows, or agentic systems

· Strong hands-on experience with LLMs and prompt engineering

· Experience building agent-based architectures and autonomous workflows

· Proficiency in Python or JavaScript/TypeScript

· Experience with workflow orchestration tools (e.g., LangGraph, Temporal, Airflow, Prefect, n8n, Zapier, or similar)

· Strong experience with REST APIs, Webhooks, and event-driven systems

· Knowledge of state management, memory, and tool usage in AI agents

· Familiarity with vector databases (Pinecone, FAISS, Weaviate, Chroma)

· Understanding of AI observability, logging, and monitoring

· Strong analytical and problem-solving skills