Software Engineer, Distributed Simulation

ABOUT THE TEAM

Software Integration Environment (SIE) is a platform that makes it easy to deploy, manage, and test operational environments - including running simulations with emulated and/or live hardware assets. We operate the critical infrastructure that enables Anduril to rapidly develop, test, and deploy autonomous systems for our warfighters, across cloud and edge-connected environments.

Our platform provisions isolated, reproducible environments for simulation and integration testing at scale. It is used both internally by Anduril engineers and externally by our customers. If you are an experienced engineer who wants to build high-scale infrastructure as a product — not just operate it — and you want that work to directly compress the loop between writing software and delivering capability to the field, this is the job for you.

ABOUT THE ROLE

We are looking for a Software Engineer to work within major systems inside the SIE platform. This is a software engineering role with an infrastructure center of gravity: you will build services orchestrating compute and exposing capabilities to users as part of a coherent platform.

You will work on problems that do not have a settled answer yet, in a product that is growing quickly in both scale and number of users. We expect you to work end-to-end: design, implement, ship, operate, and then talk to the people using it. Senior engineers on this team lead projects, mentor other engineers, and are trusted to make and defend architectural decisions.

WHAT YOU'LL DO

• Design and build the backend services that provision, orchestrate, and tear down distributed test and simulation environments on Kubernetes
• Own significant subsystems of the platform end-to-end — from design through rollout, operation, and iteration with users
• Scale the platform's compute layer as demand grows, including capacity management, performance, and efficient use of expensive resources
• Improve the interfaces and abstractions through which users describe their environments, so they can express complex test topologies without needing to be Kubernetes experts
• Build for the range of environments we deploy into, including cloud and on-premise, along with the release and configuration tooling that makes those deployments repeatable
• Improve reliability and performance of a system whose workloads are heavy and short-lived, including instrumentation, monitoring, and root cause analysis when something breaks
• Raise the engineering bar through design and code review, technical mentorship, and clear technical writing
• Work directly with internal engineering teams, business lines, and external customers to understand where the platform falls short, and turn that into shipped improvements

REQUIRED QUALIFICATIONS

• 3-6 years of professional software engineering experience
• Computer Science degree or equivalent industry experience
• Strong production experience in a language such as Go, Rust, C++, Java, or Python
• Experience building and operating distributed systems or infrastructure platforms in production, including ownership of the operational side (deployment, monitoring, debugging, on-call)
• Hands-on Kubernetes experience with a deep understanding of its internals and components, such as as controllers, operators, and custom resources
• Experience with infrastructure as code and modern build and deployment tooling (e.g. Terraform, Helm, CI/CD systems)
• Demonstrated ability to own an ambiguous, cross-cutting project end-to-end and drive it to production
• Strong written and verbal communication — you can write a design document that a skeptical reader can evaluate
• Eligible to obtain and maintain an active U.S. Secret security clearance

PREFERRED QUALIFICATIONS

• You have a bias for action and taking ownership. You have a track record of fixing a problem when you see one, including problems that are not formally yours.
• Experience building a platform or developer tooling product with real users — internal or external — and iterating based on their feedback
• Experience with KubeVirt, qemu, virtualization or hypervisor technologies
• Experience managing Kubernetes clusters of hundreds of nodes, including capacity management and autoscaling
• Experience with simulation, modeling, robotics testing, or hardware-in-the-loop systems
• Experience with cloud infrastructure across more than one provider (AWS, Azure), and with on-premise deployment
• Experience or interest working in monorepos with modern build systems like Bazel, Buck, Nix, etc.
• Experience designing and implementing APIs using gRPC/protobuf or similar technologies
• Knowledge of performance improvement techniques, metrics and alerting
• Experience with low-level frameworks, Linux and databases
• Active U.S. Secret security clearance