Cloud Platform Engineer

We are seeking a Senior Cloud Platform Engineer to architect, build, and scale the cloud and edge infrastructure powering a growing fleet of AI-driven robotic systems. This is not a traditional DevOps role focused solely on web applications. You will be responsible for infrastructure that supports real-world robotic operations, secure fleet connectivity, remote device management, AI/ML training workloads, and mission-critical cloud services.

In this role, you will help design and operate the platforms that connect autonomous robotic systems in the field with cloud-based services, data pipelines, and machine learning infrastructure. You’ll work closely with software, robotics, and AI engineers to ensure reliable operation of distributed systems deployed in production environments.

This position is ideal for engineers who enjoy solving challenges at the intersection of cloud infrastructure, robotics, IoT, networking, and artificial intelligence. Responsibilities

• Architect, build, and maintain cloud-native infrastructure supporting AI-powered robotic systems.
• Design and scale AWS-based platforms from the ground up, including networking, security, compute, storage, and deployment pipelines.
• Build and support infrastructure for secure communication between cloud services and deployed robotic fleets.
• Develop and maintain CI/CD pipelines that enable rapid, reliable software releases across cloud and edge environments.
• Lead migration of services to scalable cloud architectures and containerized deployments.
• Manage fleet connectivity, remote access, VPN infrastructure, and device communications for distributed robotic systems.
• Optimize GPU infrastructure supporting machine learning training, model development, and inference workloads.
• Design monitoring, observability, and alerting systems for cloud services and field-deployed robots.
• Improve infrastructure reliability, scalability, security, and operational efficiency through automation and infrastructure-as-code practices.
• Partner with Robotics, AI/ML, Software, and Hardware Engineering teams to support product development and deployment.
• Define and track operational metrics including uptime, deployment frequency, performance, and infrastructure costs.

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 7+ years of experience designing and building AWS infrastructure from the ground up.
• Experience with Linux administration in production environments.
• Experience with Infrastructure as Code using Terraform.
• Experience developing automation and tooling using Python.
• Experience with Docker and containerized deployments.
• Experience building and maintaining CI/CD pipelines.
• Experience designing secure cloud networking architectures.
• Experience supporting production systems with high availability and reliability requirements., * Experience supporting robotics, autonomous systems, IoT platforms, or connected-device ecosystems.
• Experience managing GPU clusters or distributed compute infrastructure.
• Experience with fleet orchestration and large-scale device management.
• Experience with Kafka, MQTT, WebSockets, or similar real-time communication technologies.
• Experience with SQL, Redis, time-series databases, and data retention strategies.
• Experience with cloud observability platforms such as Prometheus, Grafana, ELK/OpenSearch, or similar tools.
• Experience with VPN technologies, 5G networking, and edge computing environments.
• Experience supporting AI/ML infrastructure and training pipelines.
• Strong ownership mindset with the ability to lead infrastructure initiatives from architecture through production deployment.

Key Technologies

AWS Terraform Python Linux Docker CI/CD Kubernetes (Preferred) MQTT Kafka WebSockets Redis SQL GPU Infrastructure Networking VPN Observability AI/ML Infrastructure Robotics IoT Location

Austin, Texas (On-site)

Note: This role is focused on building infrastructure for real-world AI-powered robotic systems and connected device fleets. Candidates should have experience architecting cloud environments from scratch and be excited by challenges involving robotics, IoT, distributed systems, and machine learning infrastructure.