Sr Systems Engineer I (DevOps, Agentic AI)

CSX Transportation•Jacksonville, FL

1d•Onsite

About The Position

Performs advanced systems and infrastructure engineering functions, including planning, designing, and implementing cloud and on-premise platform solutions. This includes container orchestration (Kubernetes/OpenShift), servers, storage, networking, and backup solutions. Leads the design and implementation of highly available, scalable, and resilient infrastructure aligned with enterprise architecture standards, including multi-region deployments and disaster recovery strategies. Develops and maintains Infrastructure as Code (IaC) and Configuration as Code to automate the provisioning and management of infrastructure and application platforms. This role blends systems engineering, software development, DevOps practices, and emerging AI-enabled automation capabilities to deliver reliable, scalable, and intelligent solutions across the enterprise.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience)
5+ years of experience in systems engineering, infrastructure engineering, or DevOps roles
Strong experience with Kubernetes and/or OpenShift
Strong experience with Linux system administration
High School Diploma/GED with 10+ years of relevant experience
Experience deploying and maintaining enterprise container platforms (OpenShift, Rancher, EKS, GKE)
Strong Linux administration skills (filesystem, networking, permissions, logging, scheduling)
Understanding of networking fundamentals including switching, routing, and load balancing
Familiarity with infrastructure performance, capacity planning, and forecasting
Experience with Infrastructure as Code (Terraform) and configuration management tools (Ansible, Ansible Automation Platform)
Experience with CI/CD pipelines and automation frameworks (Jenkins, Git-based workflows)
Experience implementing GitOps patterns using tools such as ArgoCD
Experience leveraging APIs and scripting to automate operational processes.
Proficiency in Java and/or Python for building automation, services, and integration tooling
Experience with scripting and automation (Python, Ansible, PowerShell)
Understanding of application architecture and development best practices
Understanding of prompt engineering concepts and how to structure inputs to improve AI output quality
Familiarity with reusable AI “skills,” prompt patterns, or workflow-based automation
Awareness of agentic AI concepts, including orchestration of multi-step tasks using AI agents
Familiarity with tool integration models (e.g., MCP-style approaches) for connecting AI systems to external services
Interest in applying AI to improve developer productivity, automation, and operational efficiency
Participation in a rotating on-call schedule, including support outside standard business hours

Nice To Haves

5+ years of Kubernetes/OpenShift administration in enterprise environments
Experience with cloud platforms (Azure preferred)
Microsoft Azure Administrator (AZ-104) certification
Red Hat Certified Engineer (RHCE) or equivalent Linux certification
Experience with CI/CD and GitOps tooling (Jenkins, ArgoCD)
Experience developing automation using Java or Python
Exposure to AI-assisted development, prompt engineering, or intelligent automation frameworks

Responsibilities

Design, implement, and manage enterprise Kubernetes/OpenShift platforms with a focus on resiliency, scalability, and operational efficiency
Define and maintain platform standards, including lifecycle management, patching, upgrades, and policy enforcement
Engineer infrastructure and operational workflows as code, driving automation, self-healing, and scalability (using tools like Terraform, Kubernetes Operators, etc.)
Develop, maintain, and evolve internal platforms and tools to simplify deployment, monitoring, and operational health, improving the experience for application development teams.
Collaborate across teams (MidTier, Dev, Security) to deliver secure, performant, and highly-available systems.
Design and implement CI/CD pipelines using tools such as Jenkins
Support GitOps deployment models leveraging tools such as ArgoCD
Develop Infrastructure as Code (Terraform) and Configuration as Code (Ansible) to automate provisioning and management
Automate installation, configuration, and lifecycle management of Kubernetes and supporting infrastructure
Implement monitoring, logging, and reporting to ensure system health and performance
Develop and maintain automation tools, services, and APIs using Java and/or Python
Build scripts and reusable automation to improve platform reliability and developer productivity
Collaborate with development teams to enable efficient application deployment and integration
Apply software engineering best practices, including modular design, testing, and version control
Leverage AI-assisted development tools to accelerate engineering workflows and improve productivity
Apply prompt engineering techniques to create effective, repeatable interactions with AI tools for automation and problem solving
Contribute to development and reuse of standardized AI “skills” or prompt patterns for engineering tasks
Demonstrate familiarity with agentic AI concepts, including multi-step workflows driven by AI agents and tool integration
Understand how external tools and services can be integrated into AI-driven workflows (e.g., MCP-style tool integration and context sharing)
Evaluate opportunities to incorporate AI-driven automation into infrastructure and DevOps processes
Lead or contribute to infrastructure design aligned with enterprise architecture, including high availability and disaster recovery
Establish project milestones and drive execution to meet time, cost, and quality objectives
Analyze, design, and implement solutions in complex and evolving environments
Provide technical leadership and guidance across teams.
Investigate and resolve complex service issues across systems, platforms, and teams
Perform root cause analysis and implement preventative solutions
Participate in on-call rotation and provide production support
Maintain operational documentation, standards, and runbooks
Mentor team members and share knowledge across the organization
Influence stakeholders, partners, and peers on infrastructure and platform best practices
Stay current with industry trends, including DevOps, cloud-native platforms, and AI engineering practices
Drive continuous improvement and innovation across systems and processes