Lead Kubernetes Architect (AKS and GKE)

Humana

5d•$142,300 - $195,700•Remote

About The Position

Humana is seeking a Lead Kubernetes Architect to lead the architecture, engineering standards, and lifecycle strategy for enterprise Kubernetes platforms, primarily Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE). The role advances container platform maturity and enables secure, scalable, resilient, and highly automated Kubernetes capabilities across cloud environments. The architect partners with Cloud Engineering, Security, Network, Platform, SRE, DevOps, and application teams to define reference architectures, establish best practices, guide roadmap execution, and support Day 2 operations. This hands-on architecture leadership role covers multi-cluster design, resiliency, security controls, automation, observability, AI/ML-enabled operations, and GitOps delivery, while shaping standards, resolving complex technical issues, mentoring engineers, and driving enterprise platform adoption. The position is remote, with occasional travel to Humana offices for training or meetings. Home or hybrid home/office employees must have self-provided internet service with at least 25 Mbps download and 10 Mbps upload, and work from a dedicated space that protects member PHI/HIPAA information. The position is scheduled for 40 hours per week.

Requirements

5 or more years of experience in software engineering, platform engineering, cloud engineering, or infrastructure engineering.
Demonstrated enterprise experience architecting, implementing, and supporting Kubernetes platforms, including AKS, GKE, and/or EKS.
Hands-on experience building and deploying cloud infrastructure through CI/CD and Infrastructure as Code in Azure, GCP, or AWS.
Experience developing and operationalizing a Kubernetes lifecycle support model, including upgrades, support, reliability, and Day 2 operations.
Strong Kubernetes architecture fundamentals, including cluster design and provisioning, networking and ingress, load balancing, RBAC and identity integration, pod security and policy enforcement, certificate and secret management, monitoring, logging, and troubleshooting.
Experience optimizing Kubernetes resource utilization, scaling strategies, and cluster capacity management in enterprise environments.
Experience leading engineering initiatives in Agile delivery environments and managing work through tools such as Azure DevOps.
Strong problem-solving skills and ability to resolve complex technical challenges in fast-paced environments.
Excellent written, verbal, presentation, and stakeholder communication skills.

Nice To Haves

Bachelor’s degree in Computer Science, Engineering, or a related technical field.
Advanced hands-on experience with AKS and GKE in large-scale enterprise environments.
Experience supporting production Day 2 operations for Kubernetes clusters.
Experience applying AI/ML, predictive analytics, or intelligent automation to cloud operations, cost optimization, observability, or capacity planning.
Experience with GitHub, Terraform, and GitOps delivery models such as ArgoCD.
Experience with enterprise platform tooling such as Dynatrace, Prisma Cloud/Twistlock, HashiCorp Vault, Splunk, JFrog Artifactory, and Apigee.
Familiarity with service mesh, backup/recovery tooling, policy enforcement, and cluster security controls.
Experience with container technologies such as Docker.
Working knowledge of application and data platform dependencies, including APIs and relational databases such as SQL.
Cloud certifications in Azure, Google Cloud, or AWS.
Kubernetes certifications such as CKA, CKAD, or CKS.

Responsibilities

Lead architecture, design, implementation, production deployment, and lifecycle management of enterprise Kubernetes platforms across AKS and GKE.
Define and maintain Kubernetes reference architectures, design standards, and reusable patterns for secure, scalable, and resilient container hosting.
Develop and execute a Kubernetes product maturity roadmap aligned with Humana’s Cloud Platform strategy and business priorities.
Design multi-cluster, multi-region, and highly available deployment models, including failover and disaster recovery where required.
Lead new Kubernetes platform capabilities from concept through design, build, validation, release, and operational support.
Drive Infrastructure as Code, GitOps, and CI/CD delivery models for Kubernetes platform provisioning and workload enablement.
Partner with cross-functional teams to onboard applications and improve developer experience, security, and operational consistency.
Facilitate technical workshops, architecture reviews, roadmap sessions, whiteboarding sessions, and design reviews.
Identify and implement AI/ML-driven enhancements for operations, incident detection and remediation, cost reduction, and operational efficiency.
Apply intelligent automation to capacity forecasting, workload placement, anomaly detection, rightsizing, and platform performance tuning.
Use data-driven insights to inform scaling, utilization management, and service reliability decisions.
Define strategies for platform efficiency through predictive analytics, automation, and continuous optimization of cluster and workload resources.
Optimize CPU, memory, storage, node pools, autoscaling policies, and workload scheduling.
Establish and manage capacity planning for Kubernetes clusters and supporting network dependencies.
Monitor and improve cluster utilization, node health, and workload distribution to reduce waste, prevent resource contention, and maintain stability.
Partner with network and platform teams on ingress, egress, load balancing, DNS, traffic management, and cluster networking reliability.
Define proactive thresholds, alerts, and remediation patterns to prevent capacity-related incidents and support reliable growth.
Establish and enforce Kubernetes best practices for networking, ingress, load balancing, identity and access management, certificate management, pod security, policy controls, and observability.
Align platform designs with enterprise standards for cloud onboarding, security, automation, and operational readiness.
Drive resiliency through autoscaling, upgrade planning, health monitoring, rollback strategies, and operational guardrails.
Support compliance-aligned architecture decisions, including secure defaults and approved platform integrations.
Define and evolve the Kubernetes lifecycle support model, including provisioning, upgrades, patching, deprecation, Day 2 operations, support processes, and service ownership boundaries.
Lead troubleshooting and resolution of complex platform issues, including production-impacting incidents and cross-team escalations.
Improve platform observability, logging, alerting, and operational readiness using approved enterprise tooling.
Contribute to Kubernetes cost optimization, including cluster right-sizing, autoscaling, and non-production optimization.
Mentor junior and mid-level engineers through technical leadership, coaching, and delegation.
Provide architectural guidance to application teams, product teams, and cloud engineers deploying containerized workloads.
Build partnerships with internal stakeholders, vendors, and engineering teams to drive platform adoption and long-term success.
Lead technical demonstrations and communicate architecture decisions to technical and non-technical audiences.