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Randstad Logo Randstad · IT - Software Development

Ai - Data Engineer

Australia, Perth · Job Posted June 15, 2026
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Job Description

Our client is a highly respected, forward-thinking tertiary education institution at the forefront of digital innovation. They are currently scaling the engineering team behind their flagship AI Digital Assistant—a high-profile platform designed to transform student and staff digital experiences. We are seeking a talented AI Platform Engineer to join their dedicated Core AI Platform Team. This team is not just building a chatbot; they are responsible for maturing the assistant into a robust, enterprise-grade AI platform. The successful candidate will play a pivotal role in evolving the infrastructure, data pipelines, and evaluation frameworks that power next-generation AI experiences across the entire institution.

Job Responsibility

  • Advanced Ingestion: Extend data pipelines to extract and transform multimodal datasets into highly digestible formats for Large Language Models (LLMs)
  • Security & Governance: Implement enterprise-grade file validation and automated PII masking protocols
  • Streaming & Real-Time UX: Enhance the core platform to support low-latency streaming capabilities
  • Guardrails & Alignment: Architect mechanisms to flag irrelevant or unhelpful AI responses, continuously driving up platform accuracy
  • Evaluation Frameworks: Engineer sophisticated online and offline evaluation frameworks to track and visualize overall Platform Health
  • Telemetry & Metrics: Feed rich usage metrics and telemetry into the Data Lake to power analytics and future-proof the platform
  • Agent Capabilities: Establish AgentCore capabilities to unlock autonomous agent workflows on the upcoming roadmap
  • Developer Experience: Enable robust versioning so internal developers building on top of the platform can leverage its features with absolute confidence

Requirements

  • AWS GenAI Suite: Proven, hands-on experience with AWS Bedrock, Knowledge Bases, and AgentCore is strictly required
  • Data Engineering: Demonstrated capability in building data pipelines and managing curation/transformation processes
  • AI Evaluation: Experience engineering both online and offline evaluations using sampling and automated pipeline tests
  • Orchestration Frameworks: Deep familiarity with LangGraph and/or LangChain
  • AWS Serverless Stack: Proficiency with Step Functions, DynamoDB, Lambda, and AWS CDK
  • Languages: Dual-fluency or strong proficiency in both TypeScript and Python

Nice to have

  • Experience building MCP Servers, ACP, and A2A protocols
  • Modern DevOps practices, including Docker, ECS, CodeBuild, CodePipeline, and Linux environments
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