About the Role: As an AI Agent Specialist, you’ll build, test, and deploy intelligent agents for automation, customer support, and internal operations. You’ll work with modern frameworks and LLM orchestration tools to deliver lightweight, scalable AI agents tailored for SMEs.

What You'll Do:

• Design autonomous agents for specific use cases like customer query routing, service booking, or document handling
• Build prompt-based logic and smart chaining with LangChain, AutoGen, Flowise, etc.
• Integrate APIs (REST, GraphQL) and ensure reliable communication between agent modules
• Store and retrieve agent memory using vector databases (Chroma, Weaviate)
• Deploy apps via Hugging Face Spaces, Docker, or lightweight Streamlit interfaces

Requirements:

• 1–3 years of experience in AI, ML, or automation projects
• Solid Python skills, REST API experience, and familiarity with open-source AI tools
• Experience working with LLM frameworks like LangChain or AutoGen
• Basic frontend (HTML/CSS/JS) skills to wrap simple dashboards (optional)
• Strong problem-solving and self-motivation in remote environments

Nice to Have:

• Hands-on with Flowise, CrewAI, or similar drag-and-drop builders
• Node.js skills or Streamlit experience for rapid agent demos
• Understanding of prompt engineering techniques and token limits

About the Role: As a Senior AI Agent Architect at Asenay Tech, you’ll lead the architecture, design, and deployment of complex, multi-agent systems. You’ll play a pivotal role in scaling AI agent solutions to enterprise-grade reliability, mentoring junior developers, and shaping the roadmap of intelligent automation tools.

What You'll Do:

• Design large-scale agent architectures for real-world business and automation use cases
• Lead orchestration of LLM-based workflows using LangGraph, AutoGPT, or similar frameworks
• Ensure robustness, fault tolerance, and performance at scale
• Implement modular and reusable patterns for agent collaboration and memory handling
• Mentor and guide junior AI developers in best practices and architecture decisions
• Oversee deployments on cloud-native infrastructure (Docker, FastAPI, Kubernetes)

Requirements:

• Proven experience deploying multi-agent systems in production environments
• Deep understanding of prompt engineering, LLM orchestration, and RAG patterns
• Fluency in Python and experience with tools like LangChain, LangGraph, or CrewAI
• Cloud-native deployment skills with Docker, FastAPI, Kubernetes, and CI/CD pipelines
• Strong communication, leadership, and mentoring ability

Nice to Have:

• Familiarity with vector databases (Chroma, Weaviate, etc.)
• Experience designing self-healing agent architectures
• Contributions to open-source agentic frameworks

Application Form