Senior Kubernetes Platform Engineer - 620

DSM-H Consulting; Peoria (IL); On-site; USD 120,000 - 170,000; Full time

Job summary

DSM-H Consulting seeks an experienced architect to establish and govern a scalable Kubernetes platform for enterprise AI workloads across cloud and on‑prem environments.

You will drive secure, observable, and automated platform foundations, coordinating with AI COE and security teams to ensure reliability and governance while enabling rapid, safe deployment of AI workloads.

Qualifications

• Bachelor's degree with at least 10 years in cloud platform engineering or similar.
• Security and reliability are prioritized for enterprise Kubernetes platforms.
• CKA/CKAD/CKS certifications are preferred.

Responsibilities

• Lead design, deployment, and lifecycle management of production-grade Kubernetes platforms across hybrid environments.
• Establish secure multi-tenant platform standards that strengthen governance and workload isolation.
• Build GitOps-driven operations for provisioning, upgrades, patching, scaling, and decommissioning.
• Define platform standards for deployment, observability, and service operations.
• Embed security controls, policies, secrets management, and workload protection.
• Collaborate with AI COE and security teams to align enterprise requirements.
• Support on-call readiness, disaster recovery planning, and reliability improvements.

Skills

Kubernetes mastery

Platform administration

Security governance

Automation mindset

On-call readiness

Education

Bachelor's degree with 10+ years of experience

CKA/CKAD/CKS certifications

Tools

Terraform

Helm

Argo CD

Flux

OpenTelemetry

Job description

- 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

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 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
• 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