Full stack software engineer, java and google cloud (AI and LLM prototypes)

A healthcare-focused engineering team is hiring a full stack software engineer to build cloud-native applications that use large language models and agent-style workflows. The work is centered on Java development on Google Cloud Platform, with an emphasis on creating proof-of-concepts and prototypes that demonstrate how AI capabilities can be applied to real product and operational needs. Python experience is a plus.

Responsibilities

• Design and build full stack features that connect backend services, data components, and user-facing interfaces
• Develop backend services primarily in Java, including API design, integration patterns, and service reliability
• Build and iterate on AI-enabled prototypes using large language models, including agent-style workflows and orchestration concepts
• Create proof-of-concept implementations that validate feasibility, performance, and user value before broader production buildout
• Collaborate with cross-functional partners to translate product ideas into technical approaches and prototype plans
• Integrate cloud services on Google Cloud Platform to support AI workflows, application hosting, and data access needs
• Contribute to front-end implementation to deliver complete, end-to-end experiences
• Improve code quality through clear structure, testing practices, and documentation suitable for handoff and continued development
• Participate in technical discussions and propose practical approaches that balance speed of iteration with long-term maintainability

Required experience and skills

• Strong full stack engineering background with the ability to contribute across backend and front-end development
• Professional Java development experience building backend services and APIs
• Hands-on experience with Google Cloud Platform in an application delivery context
• Demonstrated experience building AI-focused proof-of-concepts or prototypes using large language models
• Practical understanding of agent-style approaches, including multi-step task execution, tool use, and workflow orchestration concepts
• Ability to independently drive prototype work from concept to working implementation
• Strong communication skills with the ability to explain technical decisions and prototype outcomes to mixed audiences

Additional skills (preferred)

• Python experience, especially for AI experimentation, prototyping, or data-oriented tasks
• Experience integrating AI capabilities into production-oriented services and applications

FAQ

1. What are the core responsibilities of a Full Stack Software Engineer in this role?
This role involves building end-to-end applications using Java for backend services and modern frontend frameworks. It includes developing APIs, integrating user interfaces, and deploying solutions on Google Cloud. The engineer also prototypes AI and LLM-driven features and helps transition them into production-ready systems.

2. What types of applications are typically developed in this position?
Applications may include web platforms, internal tools, and AI-powered products such as chat interfaces or intelligent workflows. These solutions often combine traditional software engineering with experimental AI capabilities. The focus is on usability, scalability, and performance.

3. How is Google Cloud used in this role?
Google Cloud services are used for hosting, data storage, and application scaling. Tools like Compute Engine, Cloud Run, BigQuery, and Vertex AI may be leveraged. The role requires understanding cloud-native architecture and deployment practices.

4. What role do AI and LLM prototypes play in this job?
AI and LLM prototypes are used to explore new product capabilities such as text generation, summarization, or conversational interfaces. The engineer builds and tests these prototypes to validate ideas. Successful prototypes may be integrated into production systems.

5. What technologies and tools are commonly used?
Backend development typically uses Java frameworks like Spring Boot, while frontend development may involve React or Angular. Python or JavaScript may be used for AI integrations. Tools like Docker, Kubernetes, and CI/CD pipelines support deployment and operations.

6. How does this role balance prototyping and production development?
The engineer rapidly builds prototypes to test ideas while maintaining a focus on scalability and maintainability. Collaboration with product and data teams helps prioritize which prototypes move to production. Code quality and testing remain important throughout.