Software Engineer, Resilience and Chaos Engineering

Intrinsic is an AI robotics group at Google aiming to reimagine the potential of industrial robotics.

Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.

Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers.

We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.

In this role, you will work to improve the stability and endurance of our robotics software platform.

You will contribute to systems that proactively identify potential problems within our APIs, SDKs, web interfaces, and cloud-to-edge communication layers.

By simulating scenarios such as AI model inference timeouts, high network latency, data pipeline congestion, and malformed input, you will ensure the platform maintains a safe and predictable state even when the environment is not.

You will be part of a specialized team in developing automated frameworks that replicate real-world disruptions, thus providing a dependable infrastructure for the developers building the next generation of AI-driven robotics.

This responsibility includes developing the necessary monitoring tools to gain deep insights into overall system health.

As a technical member of a distributed team, you will work directly with colleagues in Singapore and collaborate with world-class engineering teams in Mountain View and Munich to pursue resilience strategies and set global standards for software reliability.

How your work moves the mission forward

• Design and execute automated resilience tests focusing on service boundaries and hybrid environments (on-prem and Cloud).
• Enhance the stability of end user tools and frontend systems against latency and service interruptions.
• Contribute to platform-wide design guidelines to guarantee graceful degradation in the face of adverse conditions.
• Collaborate in developing observability tools to monitor and analyze holistic system health.