Lead Kubernetes Platform Engineer (Remote)

Overview

Some of the world’s most innovative global software and technology companies struggle to find engineering partners capable of stepping into complex environments and immediately driving meaningful outcomes. These teams need more than additional hands—they need senior engineers who can quickly understand an environment, identify the path forward, and execute without constant direction.

Enter EverOps – the premier Embedded Service Provider. We partner directly with customer engineering teams to assess and address mission-critical infrastructure, cloud, and delivery challenges.

The Challenge

EverOps is looking for a Lead Kubernetes Platform Engineer with deep Amazon EKS experience at very large scale to lead a modernization discovery, and the engineering program that follows it, for a high-scale consumer mobile platform.

You’ll be stepping into a multi-cluster production EKS estate where the largest clusters run tens of thousands of pods at peak and compute demand roughly doubles between overnight lows and daytime highs. Upgrading the estate is slow and largely manual, so the team is perpetually behind the Kubernetes release cycle. Compute is one of the largest lines in the business, and the platform backs real-time, safety-critical features where failing to scale at peak is not an option.

This role requires someone who has run Kubernetes at this scale before, can form a clear point of view on an unfamiliar estate quickly, and can turn that into a sequenced, costed plan that engineering leadership can commit to, then lead the team that delivers it.

The Mission

As a Lead Kubernetes Platform Engineer, you will join our U.S.-Based Virtual Operating Center and lead an embedded TechPod as its Pod Leader: a player-coach who sets technical direction, serves as the primary point of contact for the customer’s infrastructure leadership, and stays hands-on in the work.

Your immediate priority is leading a two-month EKS modernization discovery. You’ll baseline the production estate, map Kubernetes version and support status cluster by cluster, analyze blast radius and failure domains, and deliver the upgrade automation design, compute and capacity economics model, and prioritized roadmap needed to commit the program.

As discovery closes, your focus shifts to leading execution of the modernization program across three phases: reducing blast radius through a multi-cluster target architecture, automating the upgrade cycle so the platform stays current without heroics, and right-sizing compute, including a measured, capacity-aware move to Graviton (ARM64).