AI/ML Engineer – VRM

5 days ago

Sydney, New South Wales, Australia Synechron Full time $120,000 - $180,000 per year

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.

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