Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.

We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions

About the role

Modern autonomous system development is heavily reliant on daily, realistic, and large scale simulations to test constant software changes. Join our cloud platform team to ensure we're building efficient and reliable systems for managing these large-scale workloads.

As a cloud infrastructure engineer you'll be improving the development and deployment of our large-scale simulation infrastructure. The compute and data generation scale of our product workloads pushes the boundaries of standard cluster deployments, and you'll be at the forefront of helping build out and ensure reliability of this system. All while ensuring the deployment infrastructure is interoperable with various custom autonomy software and infrastructure used across the world.

You will work closely across the entirety of the engineering team to ensure the operational success of our backend and a variety of customer deployments. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, interact closely with users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will

Create and implement best practices for deploying and maintaining software for multiple customers across all three major cloud providers (AWS, GCP, Azure) with minimal downtime and high reliability

Monitor Applied Intuition software on deployed machines and architect solutions to any bottlenecks that are encountered

Improve developer efficiency by building internal tooling and optimizing our CI/CD systems

We're looking for someone who has

A Bachelor's degree in Computer Science, Software Engineering, or equivalent

3+ years of experience in a software engineering role working on infrastructure, monitoring, or a large scale software product

3+ years of coding experience from shell scripting (e.g., Bash) to higher-level languages (e.g., Python, C++)

Experience with microservice orchestration frameworks such as Kubernetes

Experience in the following: Golang, Python, Java, React, and C++

Experience working with containerized systems (e.g., Docker)

Nice to have

Experience utilizing open source tooling

Experience with deploying software on either public clouds (e.g., AWS) or on-premise clusters

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.