Software Engineer, DevOps, Discovery

ABOUT THE TEAM

The Discovery team at Anduril is at the forefront of incubating and maturing high-potential, software-defined, AI-native offerings that meet the toughest, newest challenges across hardware, software, space, and cyber domains. We're the architects of mission autonomy and mesh networking, delivering scalable hardware solutions that meet some of the most urgent national security needs. By working hand-in-hand with elite teams in Perception, AI, Motion Planning, Hardware, Test Engineering, Space, Networking, and Vehicle hardware, we craft cutting-edge, end-to-end systems that redefine mission success.

ABOUT THE JOB

As a DevOps Software Engineer on the Discovery team, you will solve a wide variety of problems involving networking, autonomy, systems integration, robotics, and more, while making pragmatic engineering tradeoffs along the way. Your efforts will ensure that Anduril products seamlessly work together to achieve critical outcomes. You are not a DevOps person who knows a little coding, you are a coder who knows CI/CD.

You’ll work closely with software, data, and operations engineers to turn designs into working systems—streamlining development, improving performance, and keeping production stable as we scale. You’ll also collaborate with digital, manufacturing, and corporate technology teams across Anduril in a high-tech, fast-paced culture of innovation focused on solving real problems and delivering results.

Above all, Software Engineers must be driven by a “Whatever It Takes” mindset—executing in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions to deliver successful outcomes on-time and with high quality. Not only will you build our systems, but you'll also work directly with customers to deploy it.

WHAT YOU’LL DO

• Build and Manage CI/CD Pipelines: Develop and maintain CI/CD pipelines using tools like CircleCI, GitHub Actions, and Jfrog Artifactory to ensure seamless integration and deployment of machine learning models and applications.
• Infrastructure as Code (IaC): Utilize Terraform and Ansible to automate infrastructure provisioning and management on cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
• Containerization and Orchestration: Use Kubernetes to ensure reliable deployment and scaleability of applications.
• Model Management and Deployment: Set up and maintain model registries and feature stores (e.g., MLflow, Kubeflow), and manage deployment pipelines for both batch and real-time inference.
• Monitoring and Logging: Establish comprehensive monitoring and logging solutions using tools like ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, Vector, Loki, and Grafana to ensure the smooth operation of deployment environments.
• Collaborate with Cross-Functional Teams: Work closely with development, data science, and operations teams to foster collaboration and ensure the efficient and effective deployment of machine learning models.

REQUIRED QUALIFICATIONS

• Currently possesses and is able to maintain an active U.S. Top Secret security clearance
• Strong engineering background from industry or school, ideally in areas/fields such as Computer Science, Software Engineering, Mathematics, or Physics
• 3+ years working with a variety of programming languages such as Java, Python, C++, Rust, Go, JavaScript, etc.
• Experience with CI/CD tools like GitHub Actions, CircleCI, FluxCD, Jfrog Artifactory, and Git.
• Proficiency with IaC tools (Terraform, Ansible).
• Experience with cloud platforms (Azure, AWS, GCP).
• Proficiency in containerization (Docker) and container orchestration (Kubernetes).
• Ability to quickly understand and navigate complex systems and established code bases
• A desire to work on critical software that has a real-world impact

PREFERRED QUALIFICATIONS

• Strong background with focus in Physics, Mathematics, and/or Motion Planning to inform modeling & simulation (M&S) and physical systems
• Developing and testing multi-agent autonomous systems and deploying in real-world environments
• Familiarity with observability concepts and tools.
• Knowledge of security best practices for DevOps and MLOps.