Dev SecOps Engineer

Qualifications:
Bachelor’s degree required, preferably in Computer Science, MIS, or related technical field of study.
Minimum 5+ years of prior professional Platform Engineering experience.
Excellent understanding of AWS services; including EKS, ECS, and related services
Hands-on experience with Kubernetes infrastructure and tooling, including Datadog, Argo CD, Crossplane, Helm, and Karpenter strongly preferred.
Experience with various CI/CD methodologies, container orchestration tools, and observability and performance monitoring technologies.
Good understanding of networking concepts and OSI layers.
Experience designing and implementing DevSecOps practices.
Advanced knowledge in assessing, deploying, configuring, testing, and operating AWS services using IaC tools.
Experience working in Linux environments.
Strong understanding of containers (eg: Docker) and container orchestration via Kubernetes
Demonstrated hands-on experience with Git, Python, shell scripting, and Terraform in an enterprise production environment.
Thorough understanding of change management control and the software development lifecycle, from requirements analysis to testing and deployment.
Proven experience in conducting Root Cause Analysis (RCA) of issues, with a demonstrated ability to analyze data, identify patterns, and propose effective solutions to prevent the recurrence of the issue.
Excellent verbal and written communication skills, possessing the ability to interact effectively with technical and non-technical stakeholders.
Strong analytical skill-set with demonstrated attention to detail.
Ability to work effectively in a fast-paced, dynamic and high-intensity environment including open-floor plan if applicable to the position, with timely responsiveness and the ability to work beyond normal business hours when required. 
 
Preferred Qualifications:
Experience implementing Kubernetes security controls, including eBPF-based runtime visibility or policy enforcement 
Experience supporting MLOps workloads on Kubernetes (e.g., model training, serving, pipelines, or GPU-enabled workloads) 
Experience operating across multiple Kubernetes distributions (e.g., managed cloud Kubernetes and self-managed clusters) 
Experience leveraging Open Source technologies incubated through CNCF