Senior Kubernetes Platform Engineer - 620

Position Contributions to Work Group:

- This position supports the delivery of enterprise AI capabilities through a secure, scalable, and reliable Kubernetes platform.

- The role is responsible for establishing the platform foundation required to support governed AI workloads across cloud and on-premises environments, with emphasis on operational stability, security, and enterprise scalability.

- Establish the initial Kubernetes platform foundation across cloud and on-premises environments, including core cluster patterns to support early AI workload onboarding.

- Implement baseline GitOps, access, security, and operational controls to improve consistency, reduce deployment risk, and support production readiness.

- Define an operating model for the platform, including support expectations, reliability priorities, and an approach to scale for enterprise AI workloads.

Typical task breakdown:

- Lead the design, deployment, and lifecycle management of highly available Kubernetes platforms across hybrid environments to ensure resilience, scalability, and operational consistency.

- Establish secure multi-tenant platform standards that strengthen governance, resource efficiency, and workload isolation across teams.

- Build automated, GitOps-driven platform operations for provisioning, upgrades, patching, scaling, and decommissioning to reduce risk and improve delivery speed.

- Define platform standards for deployment, observability, and service operations that improve consistency and reduce engineering friction.

- Embed security and compliance controls into the platform through policy, identity, secrets management, and workload protection practices.

- Establish observability capabilities that accelerate issue detection, improve incident response, and support data-driven reliability management.

- Own and improve platform service objectives, operational readiness, and support practices to sustain reliable production operations.

- Resolve complex platform issues across networking, storage, and runtime layers while driving long-term architectural improvements.

- Collaborate with application and security teams to standardize deployment patterns, improve reliability, and support platform adoption.

- Drive continuous improvement in automation, performance, and cost efficiency to increase platform value and reduce operational overhead.

Interaction with team:

- Working with AI COE team members that consists for platform and application developers

Collaborate with platform, security, infrastructure, and application teams to - align technical decisions with enterprise requirements.

- Work effectively with globally distributed engineering and platform teams to support delivery of a shared enterprise Kubernetes platform across time zones.

- Support operational excellence through participation in on-call practices, maintenance readiness, and disaster recovery preparedness

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Work environment:

5 days in office ( no exceptions)

Education & Experience Required:

- Bachelor’s degree with 10 years of more of experience in this capacity.

- Kubernetes Certification is a nice to have

Required Technical Skills

(Required)

- Proven success building and evolving production-grade Kubernetes platforms across cloud, on-premises, or hybrid environments.

- Demonstrated experience operating Kubernetes at scale, including responsibility for reliability, security, and platform lifecycle management.

- Deep expertise in Linux, cluster networking, and storage architecture, including the ability to diagnose issues across the infrastructure stack.

- Hands-on experience with infrastructure as code and release automation in production environments, including Terraform and Helm-based platform delivery.

- Experience using GitOps tools such as Argo CD or Flux to manage deployments and improve control, consistency, and delivery efficiency in production environments.

- Strong hands-on Kubernetes security experience, including RBAC, network policies, secrets and key management, admission or policy enforcement, and production cluster hardening in enterprise environments.

Core Technology Areas

Kubernetes & Container Platform

• Kubernetes platform administration, operations, and lifecycle management

• Helm-based release and configuration management

Infrastructure Automation

• Infrastructure as code, automation, and platform provisioning

• GitOps-driven deployment and configuration management

Cloud & Hybrid

• At least one major cloud platform, preferably AWS or Azure

• Enterprise cloud and hybrid platform environments

Security & Observability

• Platform security controls, policy enforcement, and workload protection

• Observability, monitoring, and operational readiness practices

Preferred Qualifications

Experience with enterprise Kubernetes distributions and managed services such as EKS, AKS, GKE, OpenShift, or Rancher

• Familiarity with service mesh capabilities that support traffic management, security, and platform resilience

• Exposure to modern observability frameworks, including OpenTelemetry, to support scalable monitoring practices

• Familiarity with container image security, vulnerability scanning, and software supply chain practices that strengthen overall platform security maturity

• Experience supporting enterprise AI platforms, including Accenture AI Refinery, is preferred.

• Relevant certifications such as CKA, CKAD, or CKS