Job Title: AI/ML Engineer – Virtual Relationship Manager (VRM) & Conversational Systems

Location: Sydney/ Melbourne

Job Type: Full-time(Hybrid)

Summary

We’re seeking a highly skilled AI/ML Engineer - Virtual Relationship Manager (VRM) with expertise in building scalable, intelligent conversational systems and agent frameworks. The ideal candidate will have a strong background in containerized AI agents, semantic kernel development, observability, data management, API gateway deployment, and large language model (LLM) integrations to drive innovative VRM solutions.

Key Responsibilities:

• Develop and maintain containerized AI agents using frameworks like Langgraph, LangChain, and LangFuse.
• Implement semantic kernel solutions in Python for intelligent language processing.
• Design and optimize MCP tooling workflows without direct API calls, ensuring efficient tooling development.
• Define protocols for agent-to-agent (A2A) 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.

Qualifications:

• 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.

Preferred Skills:

• Experience in protocol design for agent-to-agent communication.
• Familiarity with cloud infrastructure and serverless deployment models.
• Ability to implement secure, scalable, and maintainable AI solutions.