Senior DevOps Platform Engineer

Insight Global is assisting a client in finding a Senior DevOps Platform Engineer to modernize and scale the companies shared DevOps platform. This is a newly created role, not a backfill. The organization has strong DevOps foundations but needs a senior engineer who can move the team from one-off solutions and reactive support toward a reusable, scalable platform model. This person will build standardized capabilities that product teams can easily adopt across infrastructure provisioning, Kubernetes environments, CI/CD pipelines, security, onboarding, and disaster recovery. This is a hands-on engineering position for someone who can both define the platform strategy and build the technical solutions behind it.

Platform Engineering and Modernization * Own and evolve shared DevOps platform capabilities used by multiple product and engineering teams * Turn recurring development-team needs into reusable, automated, and supportable platform solutions * Establish platform standards, golden paths, templates, and self-service workflows * Reduce one-off implementations by creating repeatable infrastructure and deployment patterns * Help introduce an internal platform model that allows teams to consume approved tools and infrastructure more efficiently Kubernetes and AWS Engineering * Modernize and scale Kubernetes environments, with a primary focus on Amazon EKS * Improve Kubernetes networking, workload reliability, upgrades, horizontal scalability, and production readiness * Establish governance for environment isolation, admission control, policy enforcement, backup, and recovery * Improve how the organization uses Kubernetes for its microservices-based applications * Design secure and scalable solutions across AWS services including EC2, VPC, S3, IAM, RDS/Aurora, load balancing, and Lambda Infrastructure as Code and Reusable Services * Develop and maintain reusable Terraform modules and standardized environment patterns * Automate infrastructure provisioning, configuration, access, and environment creation * Build self-service capabilities that allow product teams to consume infrastructure without recreating common solutions * Establish repeatable approaches for cloud migrations and new product onboarding * Ensure infrastructure solutions meet security, reliability, and enterprise architecture standards CI/CD and Developer Enablement * Design, build, and improve CI/CD pipelines, preferably using GitLab CI/CD * Establish consistent standards for builds, testing, security checks, artifact management, deployments, and release readiness * Improve deployment traceability and reliability across environments * Partner with product teams to identify delivery friction and create scalable solutions * Automate onboarding and handoff processes through documentation, templates, and standardized workflows Security, Governance, and Reliability * Define roles, permissions, and access patterns across the DevOps platform * Implement platform guardrails using IAM, policy as code, admission controls, secrets management, and network controls * Apply tools such as Open Policy Agent, Gatekeeper, or equivalent technologies to enforce Kubernetes standards * Engineer platform observability, resilience, capacity, backup, and disaster-recovery capabilities * Collaborate with Security, SRE, Architecture, and cloud service owners to apply enterprise standards within the business unit AI-Ready Platform Enablement * Help establish secure and reusable environments for AI-enabled engineering use cases * Develop governance and access patterns that allow teams to adopt approved AI capabilities responsibly * Support reusable integrations and Model Context Protocol capabilities where appropriate * Partner with software, architecture, security, and data teams to ensure AI-related environments are supportable and scalable Technical Leadership * Remain hands-on in engineering, automation, and complex troubleshooting * Diagnose infrastructure, application, networking, deployment, and security issues across multiple layers * Prioritize root-cause correction and reusable fixes over temporary workarounds * Document technical decisions, architecture standards, and implementation practices * Mentor engineers and help reduce dependency on individual team members or external vendors * Communicate platform outcomes, technical risks, and recommendations to both technical and business stakeholders

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience
• 3+ years of hands-on DevOps, cloud, infrastructure, or platform engineering experience
• Expert-level Kubernetes experience, preferably with Amazon EKS
• Strong understanding of Kubernetes governance, admission control, policy enforcement, environment isolation, backup and recovery, networking, and horizontal scalability
• Strong AWS experience across services such as EC2, VPC, S3, IAM, RDS/Aurora, load balancing, and Lambda
• Advanced Infrastructure as Code experience using Terraform
• Experience developing reusable Terraform modules, platform automation, self-service workflows, and standardized environment patterns
• Experience designing, building, and improving CI/CD pipelines, preferably with GitLab CI/CD
• Strong automation and scripting experience using Python, Bash, or a similar language
• Software development knowledge using C#, Python, or another modern programming language
• Experience building or supporting an internal developer platform
• Experience creating golden paths, service catalogs, developer portals, or reusable infrastructure products
• Experience with Open Policy Agent, Gatekeeper, GitOps, or Argo CD
• Experience with Helm, Ansible, or similar configuration and deployment tools
• Experience with Datadog, CloudWatch, SonarQube, JFrog, Veracode, or LaunchDarkly
• Familiarity with PostgreSQL, .NET, Angular, APIs, and cloud-native microservices
• Experience with secrets-management platforms and enterprise IAM standards
• Experience supporting cloud migrations, product onboarding, or platform adoption
• Experience working in a global enterprise with distributed teams
• Familiarity with AI engineering environments, AI governance, or Model Context Protocol
• AWS, Kubernetes, Terraform, DevOps, platform engineering, or security certifications
• Experience mentoring engineers and improving technical standards across teams