Summary
✨ AI‑Generated
Join a technology transformation programme as a software engineer building production applications and intelligent automation. You will apply generative AI, large language models, and agentic techniques to complex engineering and data workflows, creating systems that can interact with tools, reason through tasks, and execute multi-step processes.
Highlights
Build production-grade applications, services, APIs, and intelligent automation while working at the intersection of traditional software engineering and emerging AI. The role offers a path for backend, full-stack, or application engineers to deepen their expertise in generative AI and agentic systems.
Description
We are looking for a Software Engineer to join a major technology and data transformation program, building software and intelligent automation that will change how engineering teams work.
This is fundamentally a software engineering role.
You'll be expected to design, build and deploy production-quality applications, services and APIs, while applying Generative AI, LLMs and agentic technologies to automate complex engineering and data processes.
You'll work in an environment where traditional software engineering meets emerging AI - building solutions that can not only assist engineers, but increasingly reason, interact with systems, make decisions and execute multi-step tasks.
This is an excellent opportunity for a Backend, Full Stack or Application Software Engineer who has an interest in AI and wants to move deeper into GenAI and agentic engineering.
What You'll Do
Design, develop and deploy production-grade software applications, services and automation frameworks.
Use Python, Java, Go or similar languages to build scalable engineering solutions.
Design and develop REST APIs, microservices and integrations across enterprise platforms.
Identify manual, repetitive or complex engineering processes and build software to automate them.
Develop AI-powered applications and agentic workflows that can interact with enterprise systems and execute multi-step tasks.
Integrate LLMs and Generative AI capabilities into existing applications and engineering platforms.
Build AI agents capable of using tools, calling APIs, retrieving information and orchestrating workflows.
Develop RAG-based applications that allow AI systems to leverage enterprise documentation, technical knowledge and data.
Experiment with AI coding assistants and emerging developer tools to improve software engineering productivity.
Build automated workflows across APIs, databases, cloud platforms and modern data environments.
Develop appropriate guardrails, human-in-the-loop controls, evaluation mechanisms and observability for AI-powered solutions.
Develop and maintain CI/CD pipelines and engineering practices that support reliable production delivery.
Work closely with software engineers, data engineers, platform engineers and product teams to turn complex problems into technical solutions.
Take ownership of solutions from architecture and development through to deployment, monitoring and continuous improvement.
Prototype emerging AI capabilities and determine how they can be transformed into reliable production software.
AI & Agentic Engineering
A major component of the role will be exploring how Generative AI can evolve from an assistant into an active software engineering capability.
You may work on:
AI agents capable of executing multi-step engineering tasks.
Agents that interact with APIs, databases and enterprise applications.
AI-powered developer productivity platforms.
Automated code generation, testing, debugging and documentation.
Intelligent incident investigation and remediation.
AI-powered data engineering workflows.
LLM-powered internal applications and developer tools.
RAG and enterprise knowledge systems.
Tool/function calling and agent orchestration.
Multi-agent workflows.
Automated workflow orchestration.
AI evaluation and monitoring frameworks.
Human-in-the-loop AI systems.
Guardrails and controls for production AI agents.
You don't need to have built every type of AI system listed above.
Strong software engineering fundamentals and demonstrated curiosity around AI are more important than having experience with every framework.
What You'll Bring
Strong commercial software engineering experience.
Strong programming skills in Python, Java, Go, Node.js or similar.
Experience building and supporting production applications and services.
Strong understanding of software design, APIs, microservices and integration patterns.
Experience with Git, CI/CD and modern software development practices.
Experience working with cloud technologies such as Azure, AWS or GCP.
Ability to design solutions, write clean maintainable code and take ownership through to production.
Strong problem-solving and analytical skills.
Ability to work collaboratively across engineering, product and business teams.
Please hit apply or reach out to me directly on colin.waters@mtr.com.au
