We are seeking a Container Platform Automation & Optimization Engineer to join our Infrastructure Platforms organization. This role focuses on designing, developing, automating, and supporting enterprise container platforms, including Kubernetes and PCF, while enabling application teams to successfully deploy and operate containerized workloads.

This is a mid-level individual contributor role for an engineer who blends software development expertise with platform engineering and automation. You will work closely with application development teams, architects, platform engineers, and infrastructure partners to automate platform capabilities, improve developer experiences, optimize containerized workloads, and enable scalable, reliable platform operations.

Above all else, you are an engineer. Curious, collaborative, and passionate about building maintainable software solutions that improve how teams consume, operate, and scale modern application platforms. You apply software engineering principles throughout the SDLC, embrace GitOps practices, and continuously seek opportunities to automate manual processes through code, platform-native capabilities, and vendor-provided tooling, including emerging AI-powered features.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical work experience. 

• 3–6 years of experience in software development, platform engineering, infrastructure automation, or related engineering disciplines. 

• Experience developing production-quality automation or software using languages such as C#, Python, Java, JavaScript, or similar modern programming languages. 

• Experience working with container platforms such as PCF, Kubernetes, OpenShift, Anthos, or comparable enterprise container technologies. 

• Experience supporting applications or platforms through the software development lifecycle, including design, development, testing, deployment, and operational support. 

• Working knowledge of Git-based source control, branching strategies, pull requests, peer review, and modern CI/CD practices. 

• Experience implementing or supporting GitOps workflows, declarative configuration management, or configuration-as-code practices. 

• Understanding of containers, container orchestration, microservices, cloud-native application patterns, and platform consumption models. 

• Experience with automation tooling, scripting, and operational workflows used to improve platform delivery and reduce manual effort. 

• Familiarity with observability concepts including metrics, logging, tracing, monitoring, alerting, and operational dashboards. 

• Ability to troubleshoot complex issues across application, platform, and infrastructure domains while coordinating with multiple technical teams. 

• Strong written and verbal communication skills with the ability to collaborate effectively across engineering teams, application development teams, architects, and business partners. 

• Demonstrated curiosity, ownership, problem-solving ability, and willingness to learn new technologies and apply them to practical engineering challenges. 

Preferred Qualifications:

• Experience supporting PCF, Kubernetes, Red Hat OpenShift, Anthos, or similar enterprise container platforms. 

• Experience with GitOps platforms such as Argo CD, OpenShift GitOps, Concourse, or comparable solutions. 

• Experience with platform-native automation capabilities, vendor-supported automation frameworks, and operational tooling. 

• Experience with Ansible, platform APIs, CI/CD automation, or similar approaches used to automate platform tasks and application onboarding. 

• Knowledge of container networking, ingress, DNS, service discovery, certificates, identity integration, and platform security concepts. 

• Experience with observability tools such as Splunk, Prometheus, Grafana, OpenTelemetry-compatible tooling, or similar platforms. 

• Familiarity with Red Hat Advanced Cluster Management, OpenShift Pipelines, Tanzu Hub, or related platform management and delivery solutions. 

• Experience using vendor-provided AI or intelligent automation capabilities to improve operational efficiency, optimization, remediation, or platform insight. 

• Financial services or other highly regulated industry experience. 

• Experience contributing to engineering standards, application enablement patterns, design documentation, and operational best practices.