Summary
✨ AI‑Generated
A senior AI engineering role focused on agentic AI and cloud integration. You will build AI agents and automated workflows using MCP, APIs, tool calling, modern agent frameworks, LLMs, RAG, Python or TypeScript, and AWS services to create scalable enterprise solutions.
Highlights
Develop sophisticated agentic AI and workflow automation solutions with modern AI frameworks, LLMs, enterprise data, and AWS. The role provides hands-on ownership across AI engineering, RAG, API integration, and cloud-native application development.
Description
Senior AI Engineer (Agentic AI & AWS Integration)
Perm Role
Sydney, Australia
• 5+ years of software engineering experience with at least 2 years in Generative AI or AI Engineering.
• Strong experience building AI agents, agent orchestration, and workflow automation solutions.
• Hands-on experience with:
• Model Context Protocol (MCP)
• API integration (REST, GraphQL, Webhooks)
• Tool calling and function calling patterns
• Agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK
• Experience with Large Language Models (LLMs) such as OpenAI, Anthropic Claude, Gemini, or open-source models.
• Strong programming skills in Python and/or TypeScript.
• Experience implementing RAG architectures and integrating enterprise data sources.
Cloud Experience (AWS Preferred)
• Strong hands-on experience with AWS services and cloud-native application development.
• Experience with AWS AI/ML services, serverless architectures, API Gateway, Lambda, ECS/EKS, and cloud integration patterns.
• Knowledge of deploying and managing scalable AI workloads in AWS environments.
Key Responsibilities :
• Design and develop AI agents and multi-agent workflows using modern Agentic AI frameworks.
• Build integrations between AI solutions and enterprise applications using APIs, MCP, web services, and cloud-native technologies.
• Develop scalable AI-powered applications, copilots, assistants, and automation solutions.
• Implement Retrieval Augmented Generation (RAG) and knowledge-based AI solutions leveraging enterprise data.
• Collaborate with business and technology stakeholders to identify, design, and deliver AI use cases.
• Ensure security, governance, reliability, and operational excellence of AI solutions.
• Drive adoption of emerging AI technologies, frameworks, and best practices.
