Infrastructure & Automation Engineer

A technology company developing a next-generation data acceleration platform is looking for an Infrastructure & Automation Engineer to be the first engineer in this area, building and maintaining the automation and infrastructure behind its core technology. This is a highly hands-on role with significant ownership and the opportunity to shape the foundations of the environment from the ground up. Responsibilities: Build robust automation frameworks for testing, validating, orchestrating, and releasing software. Develop internal tools in Python to automate complex workflows, debugging, testing, and release processes. Design and maintain CI/CD pipelines using GitHub Actions, ensuring every release meets high standards of correctness and performance. Build monitoring and observability across distributed systems using Prometheus, Grafana, and CloudWatch. Work hands-on with AWS and Kubernetes/EKS to build and operate scalable infrastructure. Investigate complex system failures and performance issues across the application, container, cloud, and Linux layers. Work closely with low-level systems and engineering teams, creating automated feedback loops that help drive system and hardware-level optimization. Requirements: 6 years of experience in Software Development, QA Automation, DevOps, or Infrastructure Engineering in cloud or distributed environments. Strong Python development skills, with experience building modular automation frameworks, tools, SDKs, or debugging systems. Hands-on AWS experience, particularly with EMR, S3, and EC2. Hands-on Kubernetes/EKS experience, including orchestration and networking. Experience building and maintaining CI/CD and automated release pipelines. Experience with observability and monitoring of distributed systems. Strong Linux and CLI skills, with the ability to troubleshoot issues across OS, containers, and infrastructure. Strong problem-solving skills and the ability to work independently in a technically challenging environment. Advantages: Experience with Apache Spark, Iceberg, or large-scale distributed data systems. Background in performance testing, benchmarking, or systems optimization. Experience working with low-level, hardware, or systems engineering teams. Show more Show less