Senior Principal Platform Engineer – Connected Aviation

Stellenbeschreibung:

Lead critical projects and coordination for the Aviation Intelligence department
Support Ascentia and FlightAware teams focused on AI/ML projects, data science, and data management
Own and evolve AWS infrastructure supporting data platform, ML training, and analytics workloads
Design, deploy, and maintain EKS-based services and Kubernetes workloads
Build and manage Terraform infrastructure across development, staging, and production environments
Design and maintain CI/CD pipelines for infrastructure and application deployment
Operate and improve Kafka/Redpanda clusters
Improve reliability, observability, and performance of prediction services
Support Dagster for data workflow orchestration
Collaborate with Data Science, ML Engineering, and Data Engineering to productionize models and data pipelines
Strengthen AWS IAM, networking, and connectivity between cloud and on-premises systems
Support cyber hardening efforts with the RTX cyber team
Identify and incrementally improve existing infrastructure and deployment patterns

Requirements

Degree in Science, Technology, Engineering or Mathematics (STEM) and minimum 10 years prior relevant experience, or an Advanced Degree in a related field and minimum 7 years of experience
Proficiency with Python
Strong experience with AWS, including EKS, IAM, VPCs, and networking
Hands-on Kubernetes experience operating production workloads
Experience managing Kafka or Redpanda in production environments
Proficiency with Terraform for infrastructure as code
Experience building and maintaining CI/CD pipelines using GitLab, GitHub Actions, or similar
Solid understanding of distributed systems, reliability, and scaling
Experience supporting production data pipelines or ML systems
Experience with observability stacks such as Prometheus, Grafana, and Thanos
Experience with Kafka Connect preferred
Experience with Rust or willingness to learn it preferred
Familiarity with Dagster, Airflow, or other modern ETL orchestration tools preferred
Background supporting ML/AI systems in production (MLOps) preferred
Experience optimizing infrastructure for performance and cost preferred
Familiarity with Iceberg, Spark, Elasticsearch, and other large-scale data processing systems preferred
Experience working in hybrid infrastructure environments preferred
Must be authorized to work in the U.S. without company immigration sponsorship now or in the future
No security clearance required

Demonstrates expertise in AWS infrastructure management, including EKS and IAM, while leading AI/ML projects and data workflows. Proficient in deploying and maintaining CI/CD pipelines and managing Kubernetes and Kafka/Redpanda clusters to enhance system reliability and performance.