backend engineer

OPPO US Research Center is seeking a talented and experienced backend engineer to join our growing team. In this pivotal role, you will be responsible for designing, developing, and maintaining scalable and high-performance RESTful APIs that serve as the backbone for our generative AI-powered Android applications.

You will work primarily with platforms like Google Cloud or Azure to bring advanced AI capabilities directly to our users’ mobile phones. This is a unique opportunity to build mission-critical services that will define how users interact with AI in a mobile platform, from concept to deployment.

Requirements

Core Development & Infrastructure

• Design, develop, and maintain scalable RESTful APIs in Python to power generative AI features
• Integrate backend services provided by the platform such as GCP Vertex AI or developed internally

Performance & Systems

• Optimize API performance and scalability for global Android users
• Contribute to architectural design of distributed systems (availability, fault tolerance)

Collaboration & Operations

• Work closely with Android and ML teams on API contracts and model integration
• Implement monitoring, logging, and security best practices for production systems

Quality & Innovation

• Ensure code quality through testing (unit, integration, E2E) and documentation
• Stay updated on generative AI and cloud technology trends

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of professional backend software development experience, with a focus on building and deploying RESTful APIs.
• Proficiency in Python and one of the associated web frameworks (e.g., Flask, Django).
• Demonstrable experience with at least one major cloud platform (AWS, Azure, or GCP)
• Experience with relational (e.g., PostgreSQL, MySQL) and/or NoSQL databases (e.g., Firestore, MongoDB).
• Solid understanding of microservices architecture, asynchronous processing, and event-driven systems.
• Experience with version control systems, particularly Git.
• Strong problem-solving skills, with the ability to debug complex systems and diagnose issues across the stack.

Preferred Qualifications:

• Master’s degree in Computer Science, AI, or a related field.
• Direct hands-on experience integrating with Google Cloud Platform’s Vertex AI APIs (e.g., PaLM, Gemini, Imagen, Codey, etc.)
• Experience with containerization technologies (Docker) and orchestration (Kubernetes, Cloud Run, GKE).
• Familiarity with CI/CD pipelines and DevOps practices.
• Understanding of fundamental machine learning and deep learning concepts, especially in the context of generative AI.
• Experience or strong interest in building APIs specifically for mobile applications (Android/iOS).
• Knowledge of data streaming technologies (e.g., Kafka, GCP Pub/Sub).
• Experience with caching technologies (e.g., Redis, Memcached).
• The ability to collaborate effectively with cross-functional teams., Amazon Web Services (AWS), Android, Android Applications, Application Programming Interface (API), Architectural Design, Artificial Intelligence (AI), Best Practices, Caching, Cellular Telephone, Cloud Computing, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Debugging Skills, Deep Learning, DevOps, Distributed Computing, Django, Docker, Documentation, Equal Employment Opportunity (EEO), Flask, GCP (Good Clinical Practices), Git, Identify Issues, Machine Learning, Microservices, Microsoft Windows Azure, MongoDB, MySQL, NoSQL, Performance Tuning/Optimization, PostgreSQL, Problem Solving Skills, Production Systems, Python Programming/Scripting Language, REST (Representational State Transfer), Redis, Scalable System Development, Software Development, Source Code/Configuration Management (SCM), Streaming Technology, System Architecture, Team Player, Unit Test, Web Application Framework, memcached

The US base salary range for this full-time position is $100,000-$200,000 + bonus + long term incentives benefits. Our salary ranges are determined by role, level, and location.