Software Engineer - Cloud

Who We Are

Carnegie Robotics designs and manufactures advanced robotics systems and components for defense, agricultural, mining, industrial, and off-road autonomy applications. Our ruggedized solutions can meet the challenges of any industry, providing effective and efficient answers for even the toughest problems.

Who We’re Looking For

We are a dynamic team committed to making the impossible possible. Our staff comes from diverse backgrounds and experience levels, fueling our ethos of collective growth and passion towards our work. We warmly welcome individuals of similar mindset to join our ranks.

For this role, we are seeking a solid engineer who can take full end-to-end ownership of cloud projects. Whether you call yourself a Cloud Engineer, a Backend Developer, or have transitioned from a Web Dev or ML background, we are looking for someone who can architect a solution, deploy the infrastructure, build the backend, and keep it running smoothly.

What You’ll Be Doing

As a Software Engineer focusing on cloud and backend infrastructure, you will be collaborating with an interdisciplinary team to support our robotics and R&D applications from the cloud side. You will "own" the end-to-end development of cloud projects. This means architecting the cloud solution, deploying the infrastructure, building proper REST APIs, coordinating with front-end developers, administrating the application, resolving user issues, and continuously optimizing for both performance and cost.

What Your Day to Day Is

• Managing and Administrating AWS: Owning AWS accounts and infrastructure (account creation, billing, etc.). You will monitor the state of deployed applications, track what is driving costs, and optimize resources.
• Backend Development: Building and maintaining robust backend services and REST APIs, primarily in Python.
• Project Management & Scoping: Speaking with management, other developers, and external users to understand requirements. You will prioritize work to address critical needs, carefully scope requests, and know when to push back or defer work.
• Troubleshooting: Quickly digging into the application to diagnose and resolve user issues, even when provided with minimal or ambiguous information, and knowing exactly what follow-up questions to ask.
• Active, Iterative Development: Navigating fast-paced, ongoing development where requirements can change quickly. You will parse out work efficiently so it can be completed without requiring large, uninterrupted blocks of time.
• Observability & Security: Implementing security best practices, supporting other developers who need direct cloud resources, and using observability tools (Grafana, Prometheus, Datadog, etc.) to keep systems healthy.
• Leveraging AI: Utilizing modern AI development tools and assistants to accelerate workflows and problem-solving.