Software Development Engineer, Applied AI Solutions; AWS

Software Development Engineer, Applied AI Solutions

Job :  | Amazon Development Center U.S., Inc.

As part of AWS Applied AI Solutions organization, we have a vision to provide business applications by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real‑world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no‑brainers to buy and easy to use.

The Physical AI team at AWS is developing infrastructure that enables customers to build digital twins, train autonomous systems, and deploy edge intelligence  these capabilities grow, the experience layer—how customers discover, interact with, and visualize their physical AI workloads—is a key part of making the platform accessible and useful.

As a Software Development Engineer on the Physical AI Experience team, you will own the full customer interaction surface: the console experience, the APIs and SDKs, and the 3D visualization layer that renders OpenUSD‑based digital twins and spatial data in the browser. You will work across the stack—from React‑based console UIs and Cloud Scape components to WebGL/WebGPU rendering pipelines to RESTful and streaming API design—building the experience that makes petabytes of spatial data and complex digital twin orchestration feel simple and intuitive.

• Design and implement the AWS console experience for the Physical AI platform, enabling customers to manage spatial data assets, configure digital twin life cycles, and monitor autonomous operations through intuitive dashboards built with Cloud Scape design system components.
• Build and maintain the public API surface and SDKs that customers and partners use to programmatically interact with the Spatial Data Management Architecture (SDMA), including REST APIs for CRUD operations, streaming APIs for real‑time spatial data, and CLI tooling for developer workflows.
• Develop the 3D visualization layer that renders OpenUSD scenes, NVIDIA RTX‑powered digital twins, and multi‑modal spatial data in the browser using WebGL/WebGPU, enabling customers to inspect, annotate, and collaborate on digital twin environments without local software installation.
• Create interactive coverage dashboards and analytics views that surface operational insights from spatial data pipelines—including processing volumes, digital twin health, edge device status, and autonomous system performance metrics.
• Define and enforce API design standards, versioning strategies, and backward compatibility practices across the Physical AI platform to ensure a consistent and composable developer experience as the service surface grows.
• Partner with Physical AI Platform engineers to translate backend capabilities into customer‑facing experiences, and with UX designers to validate interaction patterns through customer research and usability testing.
• Surface partner solution integrations within the console experience, ensuring customers can discover, activate, and navigate partner capabilities alongside native workflows without context‑switching between platforms.

A day in the life:
You’ll start your morning reviewing console telemetry—page load times, API error rates, and feature adoption metrics—to identify friction points in the customer experience. You’ll join a design review for the digital twin lifecycle management console, debating how to represent maturity transitions visually without overwhelming users who only need basic spatial data management. Mid‑morning, you’ll implement a new API endpoint for a partner integration, ensuring the request/response contract follows AWS API standards and integrates cleanly with existing SDKs.

After lunch, you prototype a WebGPU‑based point cloud renderer that lets a customer inspect their factory’s 3D spatial data directly in the console, replacing a workflow that previously required downloading gigabytes of data to a local workstation. You’ll spend the afternoon pairing with a backend engineer to design the streaming…