Full Stack Google AI Engineer

Overview

Build and scale enterprise AI solutions on Google Cloud, combining full-stack software engineering with modern AI technologies, and contribute reusable components and engineering standards for teams across the organization.

What you'll do

• Design and develop end-to-end AI-enabled applications on Google Cloud.
• Build backend services, application programming interfaces and user-facing application components.
• Integrate applications with Google AI technologies, including Vertex AI and Gemini models.
• Turn business and product requirements into practical, production-ready technical solutions.
• Build reusable components, templates and engineering patterns that can be adopted across multiple products and use cases.
• Develop applications with security, scalability, reliability, maintainability and observability in mind.
• Apply modern software engineering practices, including automated testing, continuous integration and continuous delivery.
• Work collaboratively with product teams, solution architects, AI engineers and cloud platform teams.
• Diagnose and resolve application, integration and performance issues across the solution.
• Contribute to technical documentation, coding standards, code reviews and engineering best practices.
• Share knowledge with other engineers and contribute to the continued growth of the Google Cloud and AI engineering capability.

What you'll need

• Hands-on software engineering experience using languages such as Java, JavaScript, TypeScript or similar modern programming languages.
• Experience designing and building full-stack applications and web-based application programming interfaces.
• Practical experience developing solutions on Google Cloud.
• Experience developing applications using container-based or serverless architectures.
• A good understanding of generative AI and large language model application development.
• Experience integrating AI or machine learning capabilities into applications.
• Experience with source control, automated testing and continuous integration and delivery practices.
• A good understanding of cloud-native application architecture and modern software development practices.
• Strong problem-solving skills and the ability to collaborate effectively with both technical teams and product stakeholders.

Nice to have

• Experience working with Vertex AI or Gemini models.
• Experience with Google Cloud services such as Cloud Run, Cloud Functions, identity and access management, and application programming interface management.
• Python development experience, particularly for AI or cloud-based applications.
• Experience building enterprise generative AI applications using techniques such as retrieval-augmented generation, where AI models use trusted enterprise information to improve their responses.
• Exposure to AI agents or multi-step AI applications that can use tools, data and services to complete tasks.
• Experience creating reusable software frameworks, shared engineering components or development accelerators.

Details

• Location: Uniops Bangalore Centre.