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Infrastructure Engineer

Pełny etat Praca zdalna

Data publikacji: 03.09.2026

At AeroVect, we provide autonomous driving solutions to some of the busiest airports and logistics hubs in the world. Backed by top-tier investors, AeroVect is shaping the future of structured autonomy, beginning with self-driving tow tractors.

If you have a passion for applying autonomous driving technologies to impact the flow of goods for millions of people, we want to talk to you!

You will work closely with our engineering team across the autonomy stack to ensure the operational success of our internal systems and customer deployments. Being an infrastructure specialist, you will build out infrastructure initiatives, optimize our cloud compute and storage systems, and own our administration and provisioning backbone to support new engineering projects. This role will have the opportunity to build the future of our development workflow, collaborating closely with engineers and customers.

We’re looking for a talented infrastructure engineer who is eager to bring entire modules supporting the development of our autonomous driving stack to life from the ground up as we scale with customers at some of the largest airports in the world.

Your job scope will involve selecting and working with both cutting-edge techniques as well as proven, off-the-shelf technologies to enable rapid development and continuous integration of our perception, localization, motion planning, and control capabilities for a range of airport driving scenarios, including outdoor vehicle corridor and indoor cargo terminal navigation.

The opportunity offers a technical, hands-on engineer the chance to help develop a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model.

This role will work directly with our co-founders and the Autonomy Lead.

Responsibilities

Define, lead, and own the hands-on creation of reliable data pipelines and DevOps infrastructure — expect to spend ~80% of your time performing hands-on development, with the remaining 20% integrating with our overall software stack, working with a team of world-class engineers to target aggressive milestones.; Create and implement best practices for deploying and maintaining software with high reliability and minimal downtime; Manage our data pipeline to efficiently handle processing of the largest airport datasets in the world; Improve developer efficiency by optimizing various workflows such as build systems; Help design systems to handle simulations at scale, architecting solutions to any bottlenecks encountered along the way; Monitor AeroVect software on deployed vehicles and build solutions to any bottlenecks encountered; Collaborate with the engineering team and customers at large on existing and future deployments to support all aspects of ground vehicle autonomy development, including perception, planning, and controls; Work on world-class solutions to leading infrastructure problems in autonomous airport logistics; Up to 25% travel may be required

Requirements

Experience in a DevOps role working on a large scale software product; Expertise with microservice or job orchestration frameworks, containerized systems (e.g. Docker), and big data management; Experience developing and deploying infrastructure at scale, such as on public clouds or on-premise clusters; 2+ years of experience working in either autonomous vehicles or robotics domains; Scripting experience in bash, software development experience in python & C++; Experience with Linux development & local networking; Experience with testing or developing software applications in a fast-paced environment; BS degree in Computer Science, Engineering, Mechatronics or equivalent preferred; Willingness to get hands-on and have lots of fun; MS in CS (or related discipline) + 3 years industry experience with autonomous vehicles, robotics, or similar; Background in management of big data streams; Experience working with containerization, cluster orchestration, or infrastructure management frameworks (such as Kubernetes or Docker); Experience writing drivers for various hardware interfaces; Experience with API design and complex system integrations; Familiarity with robotics software and middleware like ROS; Startup Experience
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