About the role

AI summarised

As a Senior Full-Stack Engineer in ResMed's Generative AI Center of Excellence, you will design and develop both front-end and back-end systems for AI/ML applications, including chatbots and MVPs. You will collaborate with machine learning engineers and product managers to build scalable, performant solutions using cloud technologies and modern development practices. The role involves mentoring team members, implementing best practices, and contributing to the integration of generative AI into full-stack applications.

MedTechOnsite

Key Responsibilities

Craft compelling front-end interfaces and develop high-quality backend services for GenAI products
Work with a high-performing team of machine learning engineers and architects to deliver POCs and MVPs demonstrating generative AI functionality
Support and define architecture decisions to ensure high-performance and responsive applications
Facilitate design and code reviews to enhance the collaborative development process
Work with cross-functional teams to implement guardrails around LLM input/outputs
Help mentor team members in frontend and backend development best practices

Requirements

Masters or PhD in computer science or related technical field and 3+ years of industry experience in full-stack development
Or 5+ years of industry experience in front-end and/or full-stack development
Proficiency in server-side languages such as Python and client-side languages like JavaScript
Extensive experience with cloud services (AWS preferred) and understanding of serverless architecture
Solid understanding and hands-on experience in front-end and back-end development
Experience in developing user interfaces for complex applications, including responsiveness and accessibility considerations
Knowledge of RESTful API design and microservices architecture
Experience with end-to-end testing, unit testing, and automated testing frameworks
Strong grasp of DevOps principles, including CI/CD and infrastructure as code (e.g., Terraform)
Understanding of GenAI systems and their integration into full-stack applications