Systems Engineer - Infrastructure as Code, Ansible, Terraform

the Client•Owings Mills, MD

2d•Hybrid

About The Position

The successful candidate will be responsible for developing and managing infrastructure as code (IaC), software development, continuous integration, system administration, and Linux. The candidate will be working in managing Kubernetes environments (EKS), developing and implementing tools in Python to manage and support automation of the API Management Systems (Apigee, AWS API Gateway) and Confluent Kafka within the AWS cloud environment.

Requirements

Self-driven, self-learner willing to share knowledge and participate actively in a team environment.
Ability to troubleshoot and diagnose complex issues (e.g. including internal and external SaaS/PaaS, troubleshooting network flows).
Able to demonstrate experience supporting technical users and conduct requirements analysis.
Can work independently with minimal guidance & oversight.
Experience with IT Service Management and familiarity with Incident & Problem management.
Highly skilled in identifying performance bottlenecks, identifying anomalous system behavior, and resolving root causes of service issues.
Demonstrated ability to effectively work across teams and functions to influence design, operations, and deployment of highly available software.
Knowledge of standard methodologies related to security, performance, and disaster recovery.
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
Implementation experience designing and building enterprise-scale integrations with other systems in hybrid multi-cloud environments.
Strong implementation experience with Infrastructure as Code and configuration management, including Ansible and Terraform.
Strong development experience in Python and Linux shell scripting, including building modern accelerators to enhance or supplement integration across systems.
Competent developing new solutions in one or more high-level languages, such as Java or Python.
Proven experience as a DevOps Engineer with a focus on AWS.
Strong proficiency in AWS services such as EKS, EC2, IAM, including ABAC, S3, Lambda, and VPC, with working knowledge of networking components such as VPCs, Transit Gateways, firewalls, load balancers, and similar network appliances.
Experience and subject matter expertise working with Kubernetes, specifically EKS, and Docker containerization and developing Helm charts.
Strong understanding and working knowledge of containers.
Knowledge of both physical/on-premises systems and public cloud infrastructure.
Strong understanding of Linux fundamentals and proficiency in distributed Linux environments.
Solid understanding of networking concepts, including the OSI model, with hands-on troubleshooting experience across Layers 4–7 and a good understanding of TLS protocol and TLS certificate lifecycle management.
Experience with monitoring and visualization tools such as Prometheus, Grafana, and Splunk.
Background in both Systems Engineering and Software Engineering.
Hands-on experience delivering complex software in an enterprise environment.
Experience utilizing AI developer tools, such as Kiro, Claude Code, Codex, or similar tools.
5 years of Python and Linux shell scripting.
3 years of AWS DevOps experience.

Nice To Haves

Certification in AWS (Associate Architect/DevOps); Kubernetes CKA is a plus.
Experience with Agile ways of working.

Responsibilities

Support systems engineering lifecycle activities for engineering platforms, including requirements gathering, design, testing, implementation, operations, and documentation.
Automating platform management processes through Ansible, Python or other scripting tools/languages with solid DevSecOps practices.
Troubleshooting incidents impacting the platform.
Collaborate with cross-functional teams to understand data requirements and design scalable solutions that meet business needs.
Develop documentation materials.
Participate in on-call rotations to address critical issues and ensure the reliability of data engineering systems.
Monitor, troubleshoot, and optimize the performance and reliability of engineering platforms.