Lead Kubernetes Architect

Humana is seeking a Lead Kubernetes Architect to lead the architecture, engineering standards, and lifecycle strategy for enterprise Kubernetes platforms, with a primary focus on Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE).

This role is central to advancing Humana’s container platform maturity and enabling secure, scalable, resilient, and highly automated Kubernetes capabilities across cloud environments.

The Lead Kubernetes Architect will partner across Cloud Engineering, Security, Network, Platform, SRE, DevOps, and application teams to define Kubernetes reference architectures, establish platform best practices, guide roadmap execution, and support Day 2 operational excellence.

Kubernetes Platform Architecture

• Lead the architecture, design, and implementation of enterprise Kubernetes platforms across AKS and GKE, from initial planning through production deployment and ongoing lifecycle management.
• Define and maintain Kubernetes reference architectures, design standards, and reusable platform patterns for secure, scalable, and resilient container hosting.
• Develop and execute a Kubernetes product maturity roadmap aligned to Humana’s Cloud Platform strategy and business priorities.
• Design for multi-cluster, multi-region, and highly available deployment models, including failover and disaster recovery considerations where required.

Engineering and Delivery Leadership

• Lead new Kubernetes platform capabilities from concept through design, build, validation, release, and operational support.
• Drive adoption of 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 build platform capabilities that improve developer experience, security, and operational consistency.
• Facilitate technical workshops, architecture reviews, roadmap sessions, whiteboarding sessions, and design reviews.

AI/ML, Automation, and Cost Optimization

• Identify and implement AI and ML-driven enhancements to improve Kubernetes platform operations, accelerate incident detection and remediation, and drive measurable cost reduction and operational efficiencies.
• Evaluate and apply intelligent automation for capacity forecasting, workload placement, anomaly detection, rightsizing recommendations, and platform performance tuning.
• Partner with engineering and operations teams to incorporate data-driven insights into platform scaling, utilization management, and service reliability decisions.
• Define strategies to improve platform efficiency through predictive analytics, automation, and continuous optimization of cluster and workload resources.

Kubernetes Resource Optimization and Capacity Management

• Lead the optimization of Kubernetes resources, including CPU, memory, storage, node pools, autoscaling policies, and workload scheduling to maximize efficiency and platform performance.
• Establish and manage capacity planning practices for Kubernetes clusters and supporting network dependencies to ensure adequate performance, scalability, and availability.
• Monitor and improve cluster utilization, node health, and workload distribution to reduce waste, prevent resource contention, and maintain service stability.
• Partner with network and platform teams to ensure network stability and reliability, including planning for ingress, egress, load balancing, DNS, traffic management, and cluster networking dependencies.
• Define proactive thresholds, alerts, and remediation patterns to prevent capacity-related incidents and support reliable growth across AKS and GKE environments.

Security, Reliability, and Governance

• Establish and enforce Kubernetes best practices across networking, ingress, load balancing, identity and access management, certificate management, pod security, policy controls, and observability.
• Ensure platform designs align with Humana enterprise standards for cloud onboarding, security, automation, and operational readiness.
• Drive platform resiliency through auto-scaling, upgrade planning, health monitoring, rollback strategies, and operational guardrails.
• Support compliance-aligned architecture decisions, including secure defaults and approved platform integrations.

Operations and Lifecycle Management

• Define and evolve a Kubernetes lifecycle support model, including cluster provisioning, upgrades, patching, deprecation strategy, Day 2 operations, support processes, and service ownership boundaries.
• Lead troubleshooting and resolution of complex platform issues in real time, including production-impacting incidents and cross-team escalations.
• Improve platform observability, logging, alerting, and operational readiness using approved enterprise tooling.
• Contribute to cost optimization strategies for Kubernetes environments, including cluster right-sizing, autoscaling, and non-production optimization practices.

Leadership and Collaboration

• 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 strong partnerships with internal stakeholders, vendors, and engineering teams to drive platform adoption and long-term success.
• Lead technical demonstrations and communicate architecture decisions clearly to both technical and non-technical audiences.

Required Qualifications

• 5+ 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 experience with 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 with the ability to resolve complex technical challenges in fast-paced environments.
• Excellent written, verbal, presentation, and stakeholder communication skills.

Preferred Qualifications

• 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 Day 2 operations for Kubernetes clusters in production.
• 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, 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.