goodship - Senior Platform Engineer

• Partner with engineering teams to identify workflow friction, improve developer tooling and local development environments, streamline deployment workflows, and champion engineering best practices that balance speed, quality, and reliability while further enabling AI-assisted engineering. • Drive Reliability and Observability • Design and implement observability across the platform using modern monitoring tools. Define Service Level Indicators (SLIs), Service Level Objectives (SLOs), and operational health metrics while building dashboards, alerting, tracing, and monitoring that improve system visibility, incident response, and operational excellence. • Strengthen Data Reliability • Partner with product engineering to improve the accuracy, consistency, and reliability of the data flowing through the platform. Build visibility into data quality and processing pipelines while proactively identifying and preventing data integrity issues before they impact customers. • Build for Scale • Continuously identify opportunities to eliminate bottlenecks, automate manual work, and improve engineering productivity. Help establish the platform, processes, and operational practices that enable GoodShip to scale efficiently as the engineering organization grows. • 5+ years of experience as a Software Engineer, Platform Engineer, Site Reliability Engineer, DevOps Engineer, or similar role. • Strong software engineering fundamentals with experience building production-quality systems. • Experience designing, deploying, and operating production workloads on AWS. • Demonstrated success building and maintaining modern CI/CD pipelines. • Ability to manage infrastructure using Infrastructure as Code tools such as Terraform, Pulumi, or CloudFormation. • Expertise in building developer tooling, automation, or internal engineering platforms. • Experience implementing observability using Datadog, Grafana, Prometheus, OpenTelemetry, or similar technologies. • Strong understanding of distributed systems, cloud architecture, and modern software delivery practices. • Experience defining operational metrics, SLIs, SLOs, dashboards, and alerting strategies. • A systems-thinking mindset with the ability to identify bottlenecks and improve engineering workflows. • Excellent collaboration and communication skills with the ability to influence engineering practices across teams. • Demonstrated ownership, curiosity, and a continuous improvement mindset. • Proficiency using AI development tools such as ChatGPT, GitHub Copilot, or Claude as productivity multipliers. • Experience supporting high-growth SaaS platforms, Kubernetes, ECS, Docker, release automation, PostgreSQL, event-driven architectures, or logistics and supply chain software is a plus.