Prototyping Architect; Physical AI), AWS Prototyping and AI Customer Engineering; PACE
Listed on 2026-07-16
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Software Architect
Prototyping Architect (Physical AI), AWS Prototyping and AI Customer Engineering (PACE)
Job : | Amazon Web Services, Inc.
- A97
Do you think big about how Physical AI, robotics, and simulation technologies are converging with Generative AI to reshape industrial operations, autonomous systems, and the machines of tomorrow? Would you like a career that puts you at the frontier of AI innovation—building prototypes that help customers harness digital twins, synthetic training data, and autonomous robots to solve real‑world problems at scale?
Amazon Web Services (AWS) is looking for a Prototyping Architect who thrives at the intersection of cloud computing, Generative AI, and Physical AI—someone who can turn a customer's vision of an intelligent physical system into a working prototype in weeks.
The AWS Prototyping and AI Customer Engineering (PACE) team transforms ambitious ideas into working prototypes faster than customers thought possible and we need world‑class builders who combine deep software craftsmanship with curiosity about physical systems. In this role, you’ll work hands‑on with customers to architect and build production‑ready prototypes spanning the full spectrum of modern AI—from Generative AI and agentic workflows to simulation environments, synthetic data pipelines, and robotic model training.
You’ll leverage AWS AI services, NVIDIA’s simulation and training stack, and cloud‑native architectures to rapidly deliver solutions that show what's possible when intelligence meets the physical world.
You will be a full‑stack developer comfortable spanning multiple languages and frameworks, making principled architectural decisions about agent behaviors, LLM integrations, AI‑driven simulation workflows, and digital twin architectures. You should have foundational exposure to Physical AI domains—digital twins, robotic or discrete event simulation, synthetic data generation—with the curiosity to go deeper. This role involves writing code, designing simulation architectures, and building breakthrough experiences that shape how industry and technology organizations globally adopt Physical AI.
Travel required—generally 25%.
Key job responsibilities- Architect and build working Generative AI, Agentic AI, and Physical AI prototypes directly with customers using AWS AI services (Bedrock, Sage Maker, IoT Twin Maker, IoT Site Wise) and cloud‑native architectures—including autonomous agents, RAG architectures, LLM‑powered applications, and simulation‑driven workflows that demonstrate production‑ready solutions.
- Design and build Physical AI prototypes spanning digital twin environments, discrete event simulation, robotic policy training pipelines, and synthetic data generation—leveraging tools such as NVIDIA Omniverse, Isaac Sim, AWS VAMS, and AWS‑native compute and storage services.
- Leverage AI‑driven development tools (Cursor, Kiro, Q Developer, Claude Code) to accelerate prototype development, implementing patterns like prompt engineering, function calling, agent orchestration, tool use, and simulation pipeline automation.
- Serve as a trusted technical advisor to customers on LLM selection, agent design, Physical AI architecture, and AI adoption strategy—guiding them through complex technical decisions and trade‑offs across both software‑defined AI and physical systems.
- Collaborate with Technical Program Managers, Design Technologists, and fellow Prototyping Architects to deliver customer engagements on time and with lasting impact, working across the full Physical AI flywheel from spatial data and simulation through to model training and deployment.
- Create and share reusable patterns and thought leadership through simulation frameworks, code libraries, technical content, whitepapers, blogs, and conference presentations that accelerate both Generative AI and Physical AI adoption across the AWS customer base.
- Work across the AWS ecosystem to distill customer needs and influence product features and roadmaps for Physical AI and simulation workloads, acting as a technical liaison between customers, service engineering teams, and AWS partners—including NVIDIA.
- 5+ years of design,…
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