Software Engineer, Cloud Infrastructure
a day ago
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OnsiteFull-timeEntry
Summary
Contoro Robotics is seeking a Software Engineer, Cloud Infrastructure to join their team in Austin, TX. The role involves scaling and hardening the Cloud Platform to enable real-time robot operation and system monitoring.
About the Role
As a Software Engineer, Cloud Infrastructure, you will lead the maintenance of web services, fleet network, and CI/CD pipelines. You will be responsible for migrating key services to cloud-based infrastructure, optimizing GPU resource management, and promoting software development best practices. Collaboration with software, hardware, and AI teams is essential to integrate infrastructure into the product lifecycle.
About You
Required:
- 2+ years of hands-on experience with Linux systems, Python, and Bash.
- Solid knowledge of AWS services (IAM, S3, EC2, ECR, VPC, etc.).
- Proficient with Docker, Docker Compose, and Terraform.
- Minimum B.S. in Computer Science, Engineering, or related field (or equivalent industry experience).
Preferred:
- Experience managing GPU clusters or distributed compute environments.
- Exposure to robot fleet orchestration or IoT deployment strategies.
- Familiarity with cloud-native observability stacks (e.g., Prometheus, Grafana, ELK).
Benefits
- Competitive salary and equity options in a rapidly growing startup.
- Comprehensive benefits including health, vision, dental.
- 401k match.
- Health & wellness program.
- Continuous education.
- Free Office Snacks.
- Flexible Work hours.
- Entertainment Area (ping pong).
- Pet friendly office.
- Employee Recognition Program (nectarHR).
- Opportunities for career growth in an exciting, fast-paced, and innovation-driven environment.
Contoro Robotics
Contoro Robotics is an Austin-based robotics startup that is revolutionizing industrial automation with AI-powered robots, focused on automating the unloading of floor-loaded trailer and shipping containers from trucks. Their pioneering human-in-the-loop (HITL) model ensures over 99% success in real-world applications, bridging the gap between AI limitations and the commercial viability of advanced robotics solutions.
Austin, TX