As a Senior Software Engineer on the Build and Deploy team, you will play a key role in driving large-scale Kubernetes infrastructure and architecture projects, collaborating with cross-functional teams to design and implement highly scalable, resilient, and secure clusters. In addition, you will push the boundaries of continuous integration to support deploying software hundreds of times per day to users. You will build systems that help increase the safety of deployments while also increasing the velocity of releasing new features. You will be responsible for ensuring optimal performance and stability for the entire software delivery pipeline. You will help set the direction of Build and Deploy to impact engineers across all WHOOP technology stacks. 

RESPONSIBILITIES:

• Develop and maintain WHOOP’s Kubernetes clusters running on AWS infrastructure.
• Drive architectural discussions and decision-making processes to improve  scalability, resiliency, and security in the build and deployment infrastructure.
• Lead developer productivity improvements through tooling configuration and integration. 
• Bring a security-first mindset to all planning and execution activities
• Educate other teams on solutions and frameworks available to help them improve the quality and speed of their  software delivery.
• Provide technical leadership and mentorship to junior engineers on the Build and Deploy team.
• Help shape the roadmap for build and deployment at WHOOP.

QUALIFICATIONS:

• In-depth understanding of Kubernetes architecture and components, including familiarity with container networking concepts, such as overlay networks, service mesh, and network policies.
• Knowledge of multi-cluster networking and communication patterns, including service discovery, cluster networking, and hybrid/multi-cloud operability.
• Experience developing RESTful applications in Java, C#, or Python.
• Experience gathering feedback from multiple stakeholders and prioritizing work to maximize business impact.
• Expertise in measuring the performance of workflows and using the data to remove bottlenecks.
• Willingness to learn and grow rapidly across a multitude of systems.