Staff Software Engineer, Infrastructure (Cloud)

The opportunity to grow into a technical leadership role is real as the team scales.

- Design, build, and maintain scalable data pipelines that move operational data from on-prem systems into cloud infrastructure

- Architect and manage cloud-based infrastructure (AWS) for scalable computation, data processing, and system telemetry

- Integrate on-prem and cloud data flows into a cohesive, reliable data architecture

- Build and maintain CI/CD pipelines to enable rapid, reliable software delivery and validation across simulation and real-world testing environments

- Implement and manage infrastructure-as-code (Terraform, CloudFormation) for consistent, automated provisioning

- Develop internal services and automation tools to streamline data ingestion, processing, and observability

- Establish and enforce best practices for data reliability, pipeline observability, and system security

- Drive root-cause analysis for data infrastructure and pipeline issues; design long-term solutions to improve system resilience

- Collaborate with autonomy and systems engineers to define scalable data interfaces and cloud deployment strategies

- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field

- 7+ years of experience building cloud infrastructure and data systems for large-scale distributed systems

- Strong proficiency in Python with a focus on data pipeline development and automation

- Hands-on experience with Kafka, Kubernetes, and gRPC for building scalable, high-throughput data systems

- Deep expertise with AWS cloud services including compute, storage, and data processing

- Experience with CI/CD platforms (Jenkins, GitHub Actions, CircleCI)

- Proficiency with containerization and orchestration (Docker, Kubernetes)

- Experience automating deployments with Terraform or CloudFormation

- Familiarity with Git-based workflows, code review processes, and collaborative software development

- Experience integrating on-prem and cloud data flows in a hybrid infrastructure environment

- Background in data engineering for robotics, autonomous systems, or real-time operational data

- Knowledge of monitoring, logging, and alerting tools such as Prometheus, Grafana, or the ELK Stack

- Familiarity with networking, security, and distributed system performance optimization

- Experience supporting safety-critical, real-time, or high-availability systems