Lead Kubernetes Platform Engineer

EverOps•San Francisco, CA

2d•Remote

About The Position

EverOps is seeking a Lead Kubernetes Platform Engineer with deep Amazon EKS experience at very large scale to lead a modernization discovery and the subsequent engineering program for a high-scale consumer mobile platform. The role involves stepping into a complex, multi-cluster production EKS environment with significant scale and performance demands. The engineer will be responsible for assessing the current state, identifying areas for improvement, and leading the execution of a modernization program focused on reducing blast radius, automating upgrades, and optimizing compute costs, including a migration to Graviton. Success will be measured by improved cost efficiency and reduced platform engineering maintenance time. This is a player-coach role, leading an embedded TechPod and serving as the primary technical contact for customer infrastructure leadership.

Requirements

8+ years in DevOps, SRE, Platform, or Infrastructure Engineering.
4+ years operating production Kubernetes.
Prior experience in a technical lead, staff, or principal-level role.
Deep production experience with Amazon EKS at large scale (multiple production clusters, thousands of nodes, or tens of thousands of pods).
Working understanding of control plane, scheduling, networking, and API limits at scale.
Hands-on ownership of EKS version upgrades across multiple production clusters, including API deprecations, add-on compatibility, node rotation, and rollback planning.
Working knowledge of the EKS standard and extended support lifecycle.
Advanced production experience with Karpenter (v1+), including NodePools, disruption and consolidation, weighting, and instance-type flexibility.
Strong understanding of EC2 instance families and generations, CPU architecture differences, network performance limits.
Experience migrating production workloads to Graviton or other ARM64 platforms, including multi-arch container builds and performance validation.
Experience modeling compute costs and commitments (Savings Plans, Reserved Instances, Spot) and building savings cases.
Solid knowledge of the AWS VPC CNI, ingress controllers, Gateway API, service mesh, and load balancing on EKS.
Advanced proficiency with Terraform.
Experience with Helm and GitOps tooling such as Argo CD or Flux.
Comfortable using Datadog, Prometheus, Grafana, or comparable tooling.
Strong scripting ability using Python, Go, or Bash.
Demonstrated ability to enter an unfamiliar environment, surface undocumented information, and produce a defensible current-state picture and roadmap.
Ability to translate technical findings into cost, risk, and capacity terms for engineering leadership and executives.

Nice To Haves

Experience with high-traffic B2C platforms with sharp daily peaks, or with real-time, safety-critical services.
Experience designing cell-based or multi-cluster architectures.
Experience running performance-per-dollar comparisons across instance generations and architectures.
Experience operating Spot capacity for large production fleets, including interruption handling for stateful or stream-processing workloads.
Experience tuning JVM heap, garbage collection, and Kubernetes requests/limits.
Experience running Bottlerocket or similar, including node boot-time optimization.
Experience building AI agents or LLM-driven tooling for infrastructure operations.
Experience leading assessment or discovery engagements that end in a committed, funded program of work.
CKA, CKS, AWS Certified Solutions Architect – Professional, AWS Certified DevOps Engineer – Professional, or similar advanced certifications.

Responsibilities

Lead a two-month EKS modernization discovery, including baselining the production estate, mapping Kubernetes versions, analyzing failure domains, and delivering an upgrade automation design, compute economics model, and prioritized roadmap.
Lead the execution of the modernization program across three phases: reducing blast radius with a multi-cluster architecture, automating the upgrade cycle, and right-sizing compute with a move to Graviton (ARM64).
Build a complete baseline of a multi-cluster production EKS estate, covering cluster inventory, topology, workload placement, ownership, cost, and Kubernetes version/support status.
Analyze failure domains and design a multi-cluster target architecture with clear workload placement and tenancy models.
Design and implement an upgrade approach that automates the EKS upgrade cycle.
Lead instance sizing and workload-fit analysis across EC2 instance families, generations, and node sizes.
Plan and drive a phased ARM64 migration, including multi-architecture builds and performance validation.
Configure Karpenter for optimal price-performance and design safe Spot instance patterns.
Model compute, support, and commitment economics and quantify savings.
Assess and improve ingress, service mesh, CNI, GitOps, and infrastructure-as-code posture.
Quantify maintenance and toil burden and build automation to reduce it.
Define scope and success criteria for AI-assisted DevOps agent workstreams.
Lead the TechPod as a player-coach, manage the working cadence with customer infrastructure owner, and partner with AWS specialists.
Produce documentation including estate baselines, architecture designs, upgrade plans, roadmaps, and executive readouts.
Present findings and recommendations to engineering leadership.