AI System Architect

1 week ago

Sydney, New South Wales, Australia beBeeArtificial Full time $120,000 - $180,000
We are seeking a skilled Ai Software Developer to join our team. As a key member of our engineering department, you will play a critical role in the development and maintenance of containerized AI agents using frameworks like Langgraph, LangChain, and LangFuse.Job Description:

The Virtual Relationship Manager (VRM) Engineer is responsible for designing and developing intelligent language processing solutions using semantic kernel development, observability, data management, API gateway deployment, and large language model integrations.

Key Responsibilities:
  • Develop and maintain containerized AI agents using Langgraph, LangChain, and LangFuse.
  • Implement semantic kernel solutions in Python for intelligent language processing.
  • Design and optimize MCP tooling workflows without direct API calls to ensure efficient tooling development.
  • Define protocols for agent-to-agent communication, ensuring reliable and scalable interactions.
  • Implement observability solutions using Langfuse, Observe, and Obstacle for system monitoring and debugging.
  • Integrate Retrieval-Augmented Generation (RAG) techniques leveraging DynamoDB, Bedrock, and embedding models for knowledge retrieval.
  • Engineer context management and dialogue state tracking using Aurora DB.
  • Build and deploy CI/CD pipelines for efficient agent deployment and updates, utilizing Docker, ECS Fargate, and FastAPI.
  • Implement LLM as an arbitration or judgment system with ChatGPT-4 and OpenAI APIs.
  • Manage container orchestration with ECS Fargate and Docker.
  • Configure and optimize API Gateway layers with Kong Gateway for secure and scalable API management.
  • Develop strategies to tackle agent scalability and performance challenges in large-scale environments.
Requirements:
  • Bachelor's or Master's degree in Computer Science, AI, Data Science, or related fields.
  • Proven experience in building AI-powered agent systems with frameworks like LangChain, Langgraph, LangFuse.
  • Strong Python development skills, especially in semantic kernel and NLP applications.
  • Hands-on experience with DynamoDB, AWS Bedrock, embedding models, and RAG methodology.
  • Deep knowledge of containerization (Docker), orchestration (ECS Fargate), and deployment pipelines (CI/CD).
  • Familiarity with large language models (e.g., GPT-4, OpenAI API) as decision or judgment components.
  • Experience with API management tools such as Kong Gateway.
  • Expertise in system observability and monitoring (Langfuse, Observe, Obstacle).
  • Knowledge of SQL/NoSQL databases, especially Aurora DB, for context and dialogue management.
  • Strong problem-solving capabilities in scaling and optimizing agent architectures.
  • Excellent communication and collaboration skills in a fast-paced environment.

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