Chief AI Technologist

1 week ago

Melbourne, Victoria, Australia beBeeArtificialIntelligence Full time $120,000 - $180,000
AI Engineer

We are seeking an accomplished AI Engineer to join our Data & AI team. As a key driver in shaping our AI, Generative AI and Machine Learning strategies, you will engage in hands-on work with complex and diverse datasets.

You will design, deploy, and refine advanced generative AI solutions, leveraging GenAI through collaboration with cross-functional teams.

Key Responsibilities:
  • Lead the design, building, and deployment of production-grade AI solutions, focusing on Generative AI, LLMs, RAG patterns, and sophisticated agentic workflows.
  • Architect cloud-native AI systems across AWS, Azure, GCP, ensuring cost-efficient scalability via LLMOps/DevOps pipelines.
  • Oversee the development and optimization of data pipelines, APIs, and integration layers to support complex AI use cases.
  • Drive the evaluation, fine-tuning, and operationalization of models using both open-source and enterprise-grade AI tools.
  • Collaborate cross-functionally to translate complex AI concepts into strategic business solutions and drive implementation.
Requirements:
  • Experience: 4+ years of experience delivering data-driven AI and GenAI solutions in a business environment.
  • Analytical Skills: Strong problem-solving abilities and a keen analytical mindset.
  • Communication Skills: Ability to convey technical concepts clearly to non-technical stakeholders.
  • Business Acumen: Understanding of business processes and the ability to translate business problems into data-driven solutions.
  • Team Player: Ability to work collaboratively in a team-oriented environment.
  • Technical skills:
    • Strong programming skills in Python; familiarity with Java is a plus.
    • Experience with data manipulation and analysis using libraries like pandas, NumPy and SciPy.
    • Hands-on experience with AI and Agentic frameworks (LangChain, LlamaIndex, vector databases, LangGraph, CrewAI etc).
    • Working expertise and strong understanding of Cloud platforms (AWS, Azure, GCP) and containerisation technologies (Docker, Kubernetes).
    • Solid understanding of data engineering and pipelines (SQL, ETL/ELT, distributed systems) to handle large datasets and unstructured data, data cleaning, and preprocessing.
    • Understanding of SQL and NoSQL databases.
    • Familiarity with RESTful APIs and microservices.
    • Experience designing production grade AI systems
    • Experience integrating AI into enterprise systems (ERP, CRM, BI) is a plus.

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