Applied Intuition Inc.
Software Engineer - Government Infrastructure Washington, District of Columbia,
Applied Intuition Inc., Washington, District of Columbia, us, 20022
About the role
On- and off-road autonomous system development relies heavily on daily, realistic, and large scale simulations to test constant software changes. Join our team to ensure we're building efficient, reliable, and secure systems for managing these large-scale workloads on government networks. You will be tasked with improving the development, deployment, and maintenance of our large-scale simulation infrastructure on government networks (e.g. Arcus, SUNet, Platform One). The compute and data generation scale of our product workloads pushes the boundaries of standard cluster deployments. You will be at the forefront of helping build out and ensure reliability of this system, and all while ensuring the deployment infrastructure is interoperable with various custom autonomy software and infrastructure. You will work closely across the engineering, product, and government organizations to ensure the operational success of our backend at 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 on government networks for multiple customers with minimal downtime and high reliability Monitor Applied’s 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:
4+ years of experience in a software engineering role working on government networks, cloud infrastructure, monitoring, or a large scale software product 4+ years of coding experience from shell scripting (e.g. Bash) to higher-level languages (e.g. Python) Experience with microservice orchestration frameworks (e.g. Kubernetes) Experience working with containerized systems (e.g. Docker) Nice to have:
Experience utilizing open source tooling
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On- and off-road autonomous system development relies heavily on daily, realistic, and large scale simulations to test constant software changes. Join our team to ensure we're building efficient, reliable, and secure systems for managing these large-scale workloads on government networks. You will be tasked with improving the development, deployment, and maintenance of our large-scale simulation infrastructure on government networks (e.g. Arcus, SUNet, Platform One). The compute and data generation scale of our product workloads pushes the boundaries of standard cluster deployments. You will be at the forefront of helping build out and ensure reliability of this system, and all while ensuring the deployment infrastructure is interoperable with various custom autonomy software and infrastructure. You will work closely across the engineering, product, and government organizations to ensure the operational success of our backend at 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 on government networks for multiple customers with minimal downtime and high reliability Monitor Applied’s 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:
4+ years of experience in a software engineering role working on government networks, cloud infrastructure, monitoring, or a large scale software product 4+ years of coding experience from shell scripting (e.g. Bash) to higher-level languages (e.g. Python) Experience with microservice orchestration frameworks (e.g. Kubernetes) Experience working with containerized systems (e.g. Docker) Nice to have:
Experience utilizing open source tooling
#J-18808-Ljbffr