About the role

AI summarised

As a Generative AI Engineer at ResMed, you will design and deploy intelligent AI workflows on AWS to modernize legacy systems, automate testing and compliance, and improve the delivery of life-changing medical technology. You will collaborate with engineering, QA, and regulatory teams to identify high-impact AI opportunities and build scalable, secure solutions. This role requires hands-on experience with generative AI, strong software engineering skills, and the ability to translate business needs into technical implementations.

MedTechOnsite

Key Responsibilities

Build Next-Gen AI Workflows: Design and deploy Generative AI solutions that eliminate repetitive work, boost efficiency, and free teams to focus on what matters most.
Modernize Systems: Bring cutting-edge AI into ResMed’s tech stack — from fine-tuning LLMs with data flywheels to integrating with MCP servers.
Spot High-Value AI Opportunities: Identify the projects where AI will deliver the most impact, balancing customer needs, cost, and scalability.
Partner with Experts: Work side-by-side with engineers, QA teams, and regulatory specialists to translate business needs into technical solutions.
Engineer for Scale: Optimize AWS serverless infrastructure and analytics pipelines to keep workflows secure, scalable, and cost-effective.
Innovate & Iterate: Take ownership of projects end-to-end, adapt quickly based on feedback, and help teammates succeed along the way.

Requirements

Experience: 2+ years of software engineering, with hands-on experience developing and deploying generative AI solutions.
Relevant Engineering or Science degrees (Software, Computer)
Technical Strength: Proficiency in .NET, AWS serverless (Lambda, API Gateway), data analytics (Glue, Athena), and AI frameworks (PyTorch, Hugging Face).
AI Expertise: Familiarity with multi-agent systems, model fine-tuning, and building data flywheels.
Collaboration Skills: Strong product sense, ability to engage stakeholders directly, and communication skills that make complex concepts clear.
Problem-Solving Drive: You know how to design AI systems that are not just powerful but practical, measurable, and safe.
Nice to Have: UI/UX or frontend development (React, JavaScript) experience.
Nice to Have: Familiarity with JAMA or requirements management tools.
Nice to Have: Knowledge of FDA regulations, medical device testing, or integrating AI with hardware systems.