AI Agents Engineer/ Python- NO C2C
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Agents Engineer/Python with a contract length of "unknown," offering a pay rate of "unknown." It requires onsite work in "Atlanta," "Dallas," or "Seattle." Key skills include Python frameworks, AI agent integration, and cloud infrastructure experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 12, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
Corp-to-Corp (C2C)
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Seattle, WA
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🧠 - Skills detailed
#Flask #Data Pipeline #Compliance #Logging #NoSQL #Knowledge Graph #Monitoring #SQL (Structured Query Language) #Azure #Data Security #Python #Django #Scala #Security #Docker #Data Science #AWS (Amazon Web Services) #Databases #GCP (Google Cloud Platform) #Cloud #AI (Artificial Intelligence) #Database Management #FastAPI #API (Application Programming Interface) #ML (Machine Learning)
Role description
Backend/Agent Engineer – Python, AI Agents, LangGraph, MCP
Location – 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote)
Key Responsibilities:
• Backend System Development:
• Architect, implement, and maintain scalable backend services and APIs using Python (FastAPI, Flask, Django) to support AI agent operations.
• AI Agent & MCP Integration:
• Develop, deploy, and orchestrate autonomous AI agents, and leverage MCP to coordinate multiple AI models and agent workflows, ensuring seamless interoperability and orchestration.
• Agent Orchestration & Workflow:
• Utilize frameworks like LangGraph and MCP to design, compose, and manage complex agent workflows, multi-agent coordination, and state management.
• System Integration:
• Integrate external data sources, third-party APIs, vector databases, and machine learning models to enhance agent capabilities.
• Performance & Reliability:
• Optimize system performance, ensure high availability, and implement robust logging, monitoring, and error-handling solutions.
• Collaboration:
• Work cross-functionally with front-end developers, data scientists, and product teams to translate requirements into technical designs and deliverables.
• Security & Compliance:
• Implement best practices for data security, privacy, and compliance in all backend operations.
Required Skills & Qualifications:
• Strong experience with backend Python frameworks (FastAPI, Flask, Django), RESTful API design, and database management (SQL/NoSQL).
• Proven expertise in integrating and orchestrating AI agents, LLMs, or multi-agent systems in production environments.
• Hands-on experience with MCP (Model Composition/Coordination Platform) for coordinating and managing AI models and agent workflows.
• Familiarity with agent workflow orchestration tools such as LangGraph.
• Experience with containerization (Docker), CI/CD pipelines, and cloud infrastructure (AWS, GCP, Azure).
• Knowledge of vector databases, data pipelines, and scalable distributed systems.
• Excellent problem-solving abilities, attention to detail, and communication skills.
Preferred:
• Background in designing backend architectures for AI or data-intensive applications.
• Experience with knowledge graphs, RAG pipelines, or advanced agent coordination.
• Open-source contributions or experience with modern agent/LLM frameworks, MCP, or similar platforms.
Backend/Agent Engineer – Python, AI Agents, LangGraph, MCP
Location – 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote)
Key Responsibilities:
• Backend System Development:
• Architect, implement, and maintain scalable backend services and APIs using Python (FastAPI, Flask, Django) to support AI agent operations.
• AI Agent & MCP Integration:
• Develop, deploy, and orchestrate autonomous AI agents, and leverage MCP to coordinate multiple AI models and agent workflows, ensuring seamless interoperability and orchestration.
• Agent Orchestration & Workflow:
• Utilize frameworks like LangGraph and MCP to design, compose, and manage complex agent workflows, multi-agent coordination, and state management.
• System Integration:
• Integrate external data sources, third-party APIs, vector databases, and machine learning models to enhance agent capabilities.
• Performance & Reliability:
• Optimize system performance, ensure high availability, and implement robust logging, monitoring, and error-handling solutions.
• Collaboration:
• Work cross-functionally with front-end developers, data scientists, and product teams to translate requirements into technical designs and deliverables.
• Security & Compliance:
• Implement best practices for data security, privacy, and compliance in all backend operations.
Required Skills & Qualifications:
• Strong experience with backend Python frameworks (FastAPI, Flask, Django), RESTful API design, and database management (SQL/NoSQL).
• Proven expertise in integrating and orchestrating AI agents, LLMs, or multi-agent systems in production environments.
• Hands-on experience with MCP (Model Composition/Coordination Platform) for coordinating and managing AI models and agent workflows.
• Familiarity with agent workflow orchestration tools such as LangGraph.
• Experience with containerization (Docker), CI/CD pipelines, and cloud infrastructure (AWS, GCP, Azure).
• Knowledge of vector databases, data pipelines, and scalable distributed systems.
• Excellent problem-solving abilities, attention to detail, and communication skills.
Preferred:
• Background in designing backend architectures for AI or data-intensive applications.
• Experience with knowledge graphs, RAG pipelines, or advanced agent coordination.
• Open-source contributions or experience with modern agent/LLM frameworks, MCP, or similar platforms.
