AI Engineer

Build the AI layer that sits behind one of Australia's most recognised consumer brands, across their app, chatbot, web, and contact centre.

You'll design and deploy production-grade GenAI and agentic solutions on AWS Bedrock, working across digital channels and contact centre tooling. Near-term deliverables include call and messaging summarisation, LLM-assisted natural language understanding, and a damaged baggage agentic workflow. This is early-stage work with real delivery targets already on the board.

You'll be working 2-3 days a week on-site, embedded in an enterprise environment that's genuinely at the start of its AI build. The stack is AWS-native throughout: Bedrock, Lambda, OpenSearch, ECS/EKS, EventBridge, and SageMaker AI Studio. You'll pick foundation models (Claude, Nova, Llama) based on the use case, build RAG pipelines against vector databases, and wire agents into live enterprise systems via APIs and MCPs. The infrastructure side sits alongside the engineering work, so comfort with Terraform or CDK matters here too.

There's real autonomy in this role. Delivery timelines are set, but how you scope and sequence the work is largely yours to own. You'll need to explain your technical decisions to non-technical stakeholders and hold your own in conversations with enterprise architects. The team is building AI governance and evaluation frameworks from scratch, so if you've done red-teaming, prompt regression testing, or observability setup in a prior role, that experience will land immediately.

What You'll Do

• Design and deploy LLM solutions on AWS Bedrock, including RAG architectures, prompt engineering, and agentic workflows using frameworks like LangChain, LlamaIndex, or Strands.
• Build multi-agent orchestration patterns and production-grade agentic solutions connected to real enterprise systems and data sources.
• Develop LLM evaluation and testing frameworks covering hallucination rates, latency, token efficiency, and agent behaviour validation.
• Embed observability and responsible AI controls across AI pipelines, including Bedrock Guardrails, content safety policies, and compliance with AI governance standards.

What You'll Need

• Hands-on production experience with AWS Bedrock, including Agents, Knowledge Bases, Guardrails, and Model Invocation.
• Proficiency in Python with async patterns, plus experience with RAG pipelines and vector databases such as OpenSearch, FAISS, or Pinecone.
• Demonstrated experience connecting GenAI capabilities and agents to real-world applications, not just proof-of-concept builds.
• Familiarity with AWS infrastructure services (Lambda, S3, API Gateway, ECS/EKS, EventBridge) and IaC tooling like Terraform or CDK.

About the Company

They're one of Australia's largest and most recognised enterprises, operating at significant scale across consumer digital channels and contact centre operations. The AI function is early-stage, which means you're building the foundations, not maintaining someone else's work.

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