Staff Software Engineer, Infrastructure (Cloud)

Accountabilities:
As a Staff Software Engineer, Infrastructure (Cloud), you will design, build, and optimize the cloud systems and data infrastructure that support advanced autonomous technology platforms. You will drive technical excellence by creating reliable architectures, improving operational resilience, and enabling engineering teams to deliver faster. Design, develop, and maintain scalable data pipelines that transfer operational data from on-premise environments into cloud infrastructure. Architect and manage cloud-based systems supporting computation, data processing, telemetry, and large-scale distributed workloads. Build reliable hybrid data architectures connecting physical systems with cloud platforms. Develop and maintain CI/CD pipelines that support efficient software delivery, simulation workflows, and real-world validation environments. Implement infrastructure-as-code solutions using tools such as Terraform and CloudFormation to automate and standardize cloud provisioning. Create internal services, automation tools, and frameworks that improve data ingestion, processing, monitoring, and operational efficiency. Establish best practices around data reliability, observability, security, and infrastructure scalability. Lead root-cause analysis for infrastructure and pipeline issues while implementing long-term solutions to improve system resilience. Collaborate with autonomy, software, and systems engineering teams to define scalable interfaces and cloud deployment strategies. Provide technical leadership by influencing architecture decisions, mentoring engineers, and helping establish engineering standards. Requirements: The ideal candidate is a highly experienced infrastructure engineer with strong expertise in cloud systems, distributed architectures, and data engineering. You should be comfortable owning complex technical challenges, designing systems from the ground up, and collaborating across engineering disciplines. Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field. 7+ years of experience building cloud infrastructure and data systems for large-scale distributed platforms. Strong programming skills in Python, particularly for automation and data pipeline development. Extensive experience with AWS cloud services, including compute, storage, and data processing solutions. Hands-on experience with Kafka, Kubernetes, and gRPC for high-throughput and scalable data systems. Strong knowledge of containerization and orchestration technologies, including Docker and Kubernetes. Experience building and managing CI/CD pipelines using platforms such as Jenkins, GitHub Actions, or CircleCI. Experience automating infrastructure deployment through Terraform, CloudFormation, or similar infrastructure-as-code tools. Familiarity with Git workflows, code reviews, and collaborative software development practices. Experience designing hybrid cloud and on-premise data architectures is highly preferred. Background in data engineering for robotics, autonomous systems, or real-time operational environments is a plus. Knowledge of monitoring and observability tools such as Prometheus, Grafana, or ELK Stack. Understanding of networking, security, distributed system optimization, and high-availability architectures. Experience supporting safety-critical, real-time, or mission-critical systems is highly valuable. Benefits: Fully remote work flexibility with opportunities across multiple global locations. Opportunity to build foundational infrastructure for advanced autonomous technology systems. High ownership role with the ability to influence architecture, engineering practices, and technical direction. Work alongside experienced engineers across cloud infrastructure, autonomy, and data systems. Opportunity to grow into a technical leadership position as the organization scales. Collaborative environment focused on innovation, engineering excellence, and solving complex challenges. Exposure to cutting-edge technologies across cloud computing, automation, and autonomous platforms.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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