Senior Full Stack Software Engineer, Subscriptions DevOps

The Washington Post•Washington, DC

12d•$119,700 - $199,300•Onsite

About The Position

We are looking for a Senior Full Stack Engineer to join the Subscriptions team at The Washington Post. This role spans the full application stack with a strong emphasis on the cloud infrastructure, delivery systems, and operational practices that keep our subscription products reliable and scalable. As a senior engineer, you will take ownership of complex technical work, contribute to architectural decisions, and help improve how the team builds, deploys, and operates software. The ideal candidate brings deep expertise in AWS, CI/CD, cloud infrastructure, and production operations, along with strong application development experience in Java - our primary backend language - and Node.js, and familiarity with React. We value autonomy, initiative, strong communication, and meaningful day-to-day use of AI-assisted engineering tools, including continually finding new ways to apply AI to development, automation, operations, and team effectiveness.

Requirements

BA/BS in Computer Science or a related field, or equivalent practical experience.
5+ years of hands-on AWS experience, including designing, deploying, operating, and troubleshooting production workloads.
4+ years of experience with CI/CD, deployment automation, and Infrastructure as Code in production environments.
3+ years of backend development experience with Java, including building and operating production services and APIs. Java is the team’s primary backend language.
2+ years of professional experience with Node.js, including services, automation, developer tooling, or infrastructure tooling.
Experience administering and operating self-hosted engineering platforms such as Jenkins, Airflow, or similar technologies in production environments.
Strong understanding of cloud architecture, networking, IAM, security, scalability, reliability, and operational best practices.
Experience building and maintaining Infrastructure as Code using AWS CDK, CloudFormation, Terraform, or comparable technologies.
Experience with containerized workloads and services such as Docker and ECS.
Strong production operations and observability experience, including logs, metrics, tracing, dashboards, alerting, and troubleshooting across applications and infrastructure.
Experience supporting business-critical systems through an on-call rotation, incident response, and post-incident remediation.
Strong software engineering fundamentals and the ability to contribute to application code when needed.
Demonstrated ability to independently identify, scope, and drive complex technical work with limited oversight.
Strong written and verbal communication skills, including the ability to communicate effectively upward and across organizational boundaries.
Significant hands-on use of AI-assisted engineering tools in day-to-day work. Candidates should be able to discuss concrete examples of applying AI to infrastructure, automation, software development, troubleshooting, incident investigation, documentation, or other engineering workflows.

Nice To Haves

7+ years of hands-on AWS, DevOps, SRE, or cloud infrastructure experience, including ownership of highly available, scalable production environments.
5+ years of experience designing and operating CI/CD, deployment automation, and Infrastructure as Code across multiple applications or teams.
5+ years of backend development experience with Java and 3+ years with Node.js.
2+ years of experience with React or a comparable modern frontend framework, with the ability to contribute to and support modern JavaScript/TypeScript applications when needed.
Deep experience with AWS CDK and building reusable infrastructure patterns, constructs, and deployment tooling.
Significant production experience administering and evolving Jenkins, Airflow, or comparable self-hosted engineering platforms.
Deep experience with AWS services such as ECS, Lambda, S3, RDS, IAM, CloudWatch, and related technologies.
Experience building reusable infrastructure, deployment patterns, automation, and developer tooling used across engineering teams.
Experience with observability platforms such as DataDog and AWS-native monitoring services.
Experience improving developer experience and engineering productivity through platform engineering, automation, and self-service tooling.
Experience mentoring engineers and influencing infrastructure, reliability, and operational practices across team boundaries.
Advanced use of AI-assisted engineering tools, including experience helping other engineers expand their effective use of AI across infrastructure, operations, automation, troubleshooting, and software development.

Responsibilities

Design, build, test, deploy, and operate applications and services supporting our subscription products.
Own technical solutions throughout their lifecycle, from design and implementation through deployment, observability, production support, and continuous improvement.
Design and maintain scalable, reliable AWS infrastructure using services such as ECS, Lambda, S3, RDS, IAM, CloudWatch, and related technologies.
Build and evolve Infrastructure as Code, with experience using AWS CDK strongly valued.
Design, maintain, and continuously improve CI/CD pipelines, deployment automation, and developer workflows.
Configure, operate, troubleshoot, and improve self-hosted engineering platforms such as Jenkins, Airflow, and similar systems.
Develop backend services and APIs primarily using Java, with Node.js used across supporting services, automation, and tooling.
Contribute to frontend applications built with React and modern JavaScript/TypeScript when needed.
Build automation that reduces operational overhead and improves the reliability and repeatability of development and production processes.
Establish strong observability and diagnose complex issues spanning applications, infrastructure, deployment pipelines, and third-party integrations.
Participate in the team’s on-call rotation, taking ownership of incident diagnosis, mitigation, communication, and systemic follow-up.
Identify technical debt, operational bottlenecks, and opportunities for improvement and proactively drive solutions.
Communicate technical decisions, risks, tradeoffs, and progress clearly to engineering peers, leadership, product partners, and adjacent teams.
Mentor engineers and contribute to technical standards, architecture discussions, documentation, and engineering best practices.
Use AI extensively throughout the engineering lifecycle and identify opportunities to apply it to development, infrastructure, troubleshooting, automation, incident investigation, and operational workflows.