Conversational AI Engineer

2 weeks ago

Sydney, New South Wales, Australia Synechron Full time $70,000 - $120,000 per year

We are seeking a highly skilled AI/ML Engineer with extensive experience in developing scalable, intelligent conversational systems and agent frameworks. The successful candidate will play a critical role in designing and implementing containerized AI agents, semantic kernel solutions, and integrating large language models (LLMs) to create innovative Virtual Relationship Management (VRM) solutions. The ideal candidate will possess a deep understanding of data management, observability practices, API gateway deployment, and AI model integration to drive cutting-edge AI advancements.

Key Responsibilities:

  • Design, develop, and deploy scalable AI agents and conversational systems, emphasizing containerized architectures (Docker, Kubernetes).
  • Build and optimize semantic kernel components to support intelligent agent behaviours and contextual understanding.
  • Integrate large language models (LLMs) for natural language understanding, generation, and conversational capabilities.
  • Implement observability and monitoring solutions to ensure system performance, reliability, and security.
  • Manage data pipelines, storage, and management for AI training, inference, and contextual data handling.
  • Deploy and maintain API gateways and microservices for seamless AI service integration.
  • Collaborate with cross-disciplinary teams including data scientists, software engineers, and product managers to develop innovative VRM solutions.
  • Ensure AI models and systems adhere to best practices for robustness, fairness, and ethical considerations.
  • Keep abreast of latest trends in AI/ML, NLP, agent frameworks, and cloud-native deployment strategies.

Preferred Skills & Qualifications:

  • Advanced degree (Master's or PhD) in Computer Science, AI, Machine Learning, or related field.
  • Proven experience in building and deploying containerized AI agents and microservices (Docker, Kubernetes).
  • Strong knowledge of semantic kernels, ontologies, and contextual reasoning systems.
  • Hands-on experience with large language models (e.g., OpenAI GPT, LLaMA, Bard) and their integration.
  • Familiarity with observability tools such as Prometheus, Grafana, ELK stack, or equivalent.
  • Expertise in API management, gateway deployment, and microservice architecture.
  • Experience with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines.
  • Solid understanding of data management, storage, and pipelines for AI systems.
  • Strong programming skills in Python, Java, or relevant languages for AI development.

Nice to Have:

  • Experience with VRM platforms or enterprise customer engagement solutions.
  • Knowledge of reinforcement learning, multi-agent systems, or conversational AI design principles.
  • Familiarity with ethical AI practices and governance frameworks.
  • Contributions to open-source AI projects or frameworks.

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