Sigmawave AI is a Singapore-based deep-tech AI startup and IMDA Pixel Accelerator alumnus, building within the NVIDIA ecosystem. Our core product, Terra™, is a Visual Synthetic Data (VSD) platform that converts 2D reference images into photorealistic, fully annotated 3D scenes for training AI and computer vision models.

Terra exists to close the visual and embodied data gap: in defence, homeland security, critical infrastructure, and industrial robotics, real-world data collection is often too slow, too costly, too dangerous, or simply classified. Terra lets teams generate the training data they need instead.

We're looking for a Full Stack Software Engineer to help build Terra's cloud-native 3D platform — the backend, orchestration, and browser-based scene-editing layers that turn a scene a user composes in the browser into distributed, GPU-orchestrated rendering jobs at scale.

This role combines full-stack web development, distributed backend systems, real-time communication, and 3D graphics engineering. You won't be adding features to a mature product — you'll be designing the job-state machinery, orchestration logic, and platform infrastructure this system runs on.

A platform that enables users to:

• Compose and edit 3D scenes directly in the browser.
• Configure cameras, lighting, objects, and environments.
• Submit rendering work orders to backend services.
• Automatically orchestrate distributed rendering jobs across a GPU fleet.
• Generate photorealistic images and annotations for AI model training.
• Store, manage, and retrieve generated datasets through scalable cloud infrastructure.

• Design, develop, and maintain scalable backend services using NestJS and TypeScript.
• Build modern, responsive frontend applications using React.
• Develop browser-based 3D scene editing experiences using Three.js.
• Implement real-time communication using Socket.IO.
• Design and maintain RESTful APIs and event-driven services.
• Build asynchronous processing pipelines using RabbitMQ.
• Manage distributed caching and application state with Redis.
• Design and optimize MongoDB data models, including asset metadata schemas covering provenance, licensing, and usage rights.
• Integrate S3-compatible object storage for assets, generated datasets, and project files.
• Develop scene serialization and work order generation.
• Build backend orchestration services that schedule and distribute rendering jobs — including stateful job/permutation tracking that can resume mid-execution after a restart, and resource-constrained scheduling across a GPU fleet.
• Integrate backend services with Unreal Engine rendering workers.
• Own CI/CD and deployment practices for backend and orchestration services.
• Optimize system performance, scalability, reliability, and fault tolerance.
• Collaborate with AI, graphics, and infrastructure engineers to improve the synthetic dataset generation pipeline.
• Write clean, maintainable, and well-tested code following engineering best practices.

• Strong proficiency in TypeScript.
• Professional experience with NestJS.
• Professional experience with React.
• Professional experience with Three.js.
• Experience developing interactive 3D applications using Three.js, WebGL, or similar technologies.
• Strong understanding of 3D graphics concepts, including cameras, lighting, materials, transformations, scene graphs, and rendering pipelines.
• Experience building rendering pipelines, job orchestration systems, or asynchronous processing workflows.
• Experience implementing real-time applications using Socket.IO or comparable WebSocket-based technology.
• Experience designing and consuming RESTful APIs.
• Experience with MongoDB.
• Experience with Redis.
• Experience with RabbitMQ or similar message queue systems.
• Experience with S3-compatible object storage.
• Experience with Docker and containerized deployments.
• Strong understanding of asynchronous programming and distributed system architecture.
• Experience using Git in collaborative development environments.
• Strong problem-solving and debugging skills.

• Experience with Unreal Engine, particularly headless/batch rendering (Movie Render Queue, commandlet mode) or Pixel Streaming, and integrating Unreal Engine with backend services.
• Experience with Kubernetes or container orchestration.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with GPU-aware or resource-constrained job scheduling.
• Experience building scalable backend systems for high-throughput workloads.
• Knowledge of computer vision, synthetic dataset generation, or AI/ML workflows.
• Experience optimizing graphics rendering or WebGL performance.
• Familiarity with CI/CD pipelines and DevOps practices.

Backend

• NestJS
• TypeScript
• Socket.IO
• RabbitMQ
• Redis

Frontend

• React
• Three.js
• WebGL

Database

• MongoDB

Storage

• S3-compatible Object Storage

Tools

• Git
• Docker