AeroVect - Staff Software Engineer, Infrastructure (Cloud)
Requirements
• 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 • We Prefer • 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
Responsibilities
• 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
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