.Engineering Remote (Portugal) Remote (Poland) Remote (Ukraine) PandaDoc is seeking a Lead Platform Engineer with a focus on Automation solutions to join our Platform Track At PandaDoc, engineering teams are divided into product teams, which focus on delivering new features, and the Platform Track, which provides the foundation that enables these teams to work efficiently. The Platform Track is responsible for managing infrastructure, automating workflows, and optimizing development environments to improve the development experience, increase productivity, and ensure faster, higher-quality product delivery across the organization. As a Lead Platform Engineer focused on automation, you will define and drive the technical strategy for automating processes. Your goal is to create and implement tools that streamline workflows for product teams, reduce manual efforts, and improve development and staging environments. Leading the automation strategy will enable product teams to deliver features faster and with higher quality. You will lead a team of engineers, working closely with product and development teams to identify bottlenecks, optimize workflows, and ensure that infrastructure and tools support the entire SDLC effectively. In this role, you will: Lead the development and optimization of automated solutions to reduce manual work across product teams, focusing on code quality practices, development and testing environments, services' pipelines stability, etc. Contribute to the technical strategy by providing engineering insights into the product delivery process and shaping an effective automation strategy. Improve local development environments through tools and automation, allowing developers to iterate more quickly and ensuring higher reliability and product quality. Work closely with developers and Platform Teams (DevEx, DevOps, SRE) to identify inefficiencies in development and delivery processes, proposing scalable automation solutions. Build and optimize CI/CD pipelines (Jenkins, GitLab CI) to enable seamless deployment and testing at every stage of the SDLC. Establish effective monitoring, logging, and alerting systems to provide rapid feedback and insights to developers during the testing phases. Mentor and lead a team of engineers, driving a culture of continuous improvement and automation. Build and execute a technical roadmap for a small team of engineers focused on automating processes, reducing cycle times, and improving product quality. Our stack: Service-oriented architecture, including legacy code and monolithic services (Django-based). Main stacks: Python (AsyncIO, Django) and Java (Spring Boot, Java 11, Gradle). Extensive use of AWS and Kubernetes for provisioning and deploying workloads. Cross-service communication: NATS (migrating to gRPC), Kafka, Debezium for event-driven operations, RabbitMQ for Celery, and Temporal.Io. Monitoring and tracing: Grafana stack for monitoring, alerting, and distributed tracing