Sr. DevOps Engineer, Cloud Platform

Contoro Inc.

Join Contoro Robotics – Revolutionizing Warehouse Automation with Cutting-Edge Robotics

At Contoro Robotics, we're on a mission to solve labor challenges through advanced robotic solutions. Headquartered in Austin, TX, our fast-growing startup is transforming the supply chain industry with our flagship warehouse automation technology. Our team is made up of top-tier experts in robotics, AI, and logistics, working together to push the boundaries of automation.

We’re looking for talented and ambitious individuals to join us on this journey—helping shape the future of robotics while growing alongside a world-class team. If you're passionate about innovation, problem-solving, and making a real-world impact, we want to hear from you!

Title: Senior DevOps Engineer

Intro

Contoro Robotics is an Austin-based startup revolutionizing warehouse automation with AI-powered robotic solutions tackling real industrial challenges. Our mission is to deploy scalable, human-in-the-loop autonomous systems that reliably perform in the field. As our fleet of unloading robots expands, we're looking for a talented DevOps Engineer to help scale and harden our Cloud Platform infrastructure. This role is critical to enabling real-time robot operation, system monitoring, and on-demand AI training infrastructure. You’ll own key components of our web services, networking, and CI/CD systems.

Job Responsibility

  • Cloud Platform Infrastructure

    • Lead and maintain three foundational pillars of our infrastructure:

      • Web Services: AWS-hosted and on-premise deployments

      • Fleet Network: Secure, scalable data communication with the robots

      • CI/CD Pipelines: Fast and reliable build/test/deploy automation

  • System Migration & Deployment

    • Lead the migration of key services to cloud-based infrastructure (AWS)

    • Design and maintain secure user access, containerized services, and cloud-native integrations

  • Fleet & GPU Resource Management

    • Optimize uptime and performance of GPU clusters for real-time and batch AI model training

    • Build and scale secure remote-access networking for robot fleet management

  • Metrics-Driven Optimization

    • Track and improve KPIs around build speed, service uptime, and deployment cadence

    • Ensure infrastructure performance stays within defined budget constraints

  • Best Practices & Collaboration

    • Promote software development best practices, including automation, versioning, and test coverage

    • Collaborate closely with software, hardware, and AI teams to integrate infrastructure into the product lifecycle

Qualification/Requirements

Please do not apply if you do not have direct experience designing and building AWS-driven infrastructure from scratch. It is not sufficient to have maintained existing systems.

  • Experience

    • 5+ years of hands-on experience with AWS, Linux, Terraform, and Python

    • Prior ownership or leadership of production infrastructure projects

  • Technical Expertise

    • Solid knowledge of AWS services (IAM, S3, EC2, ECR, VPC, etc.)

    • Proficient with Docker, Docker Compose, and Terraform

    • Experience with messaging and communication protocols (e.g., Kafka, MQTT, WebSockets)

    • Deep knowledge of scalable data stores (SQL, Redis, Timeseries, etc) and retention policies

    • Passion for CI/CD workflows and automated testing pipelines

  • Soft Skills

    • Strong sense of ownership, urgency, and curiosity

    • Excellent communication skills—both verbal and written

    • Ability to work collaboratively across cross-functional teams

  • Education

    • Minimum B.S. in Computer Science, Engineering, or related field (or equivalent industry experience)

  • Work Location

    • Willingness to work on-site at our Austin, TX headquarters

Preferred/Plus

  • Experience managing GPU clusters or distributed compute environments

  • Exposure to robot fleet orchestration or IoT deployment strategies

  • Familiarity with 5G hardware, VPN technologies, and network configuration

  • Familiarity with cloud-native observability stacks (e.g., Prometheus, Grafana, ELK)

How to apply

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