Description Site Reliability Engineer IIILocation: Onsite in Mount Laurel, NJDuration: Through 12/31/2026, extensions likelyWe are seeking a Site Reliability Engineer (SRE) to support cloud infrastructure, automation, reliability, security, and observability initiatives for AI/ML platform environments. This role is ideal for a mid-to-senior-level engineer with strong cloud and platform engineering experience who can drive scalability, reliability, and automation within Kubernetes-based production environments.
Responsibilities:- Support Site Reliability Engineering initiatives across AI/ML platform environments.
- Deploy, maintain, and optimize cloud infrastructure across AWS and Google Cloud Platform.
- Build, manage, and maintain Infrastructure as Code (IaC) solutions using Terraform.
- Improve platform reliability, scalability, security, and operational efficiency.
- Administer and support Kubernetes and Amazon EKS environments.
- Monitor and troubleshoot system performance using observability and monitoring tools including Prometheus, Grafana, Datadog, and Elasticsearch.
- Automate operational processes, workflows, and routine administrative tasks using Python and related tooling.
- Support and enhance CI/CD pipelines and deployment automation.
- Troubleshoot complex distributed systems and production issues in highly available environments.
- Collaborate with engineering teams to improve platform performance, monitoring, and operational resiliency.
- Work with technologies including Kubernetes, Docker, AWS, Google Cloud Platform, EKS, Terraform, Prometheus, Grafana, Datadog, Elasticsearch, MySQL, Kafka, and Python.
Requirements Qualifications :
- 4-8 years of experience in Site Reliability Engineering, DevOps, Platform Engineering, Cloud Engineering, or related disciplines.
- Strong hands-on experience with AWS cloud services.
- Hands-on Kubernetes administration and support experience.
- Expertise with Terraform and Infrastructure as Code (IaC) practices.
- Experience designing, supporting, and improving CI/CD pipelines.
- Strong observability and monitoring experience, particularly with Prometheus.
- Experience with Grafana, Datadog, Elasticsearch, or similar monitoring platforms.
- Python programming and scripting proficiency.
- Experience supporting distributed systems and large-scale, highly available production environments.
- Knowledge of algorithms, data structures, software design principles, and system troubleshooting.
- Experience with Docker containers and cloud-native platforms.
Preferred Qualifications: - Bachelor's degree in Computer Science or a related technical discipline.
- Experience supporting AI/ML platforms or infrastructure.
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