Immediate need for a talented Site Reliability Engineer. This is a 12+months contract opportunity with long-term potential and is located in Abbott Park, IL(Onsite). Please review the job description below and contact me ASAP if you are interested.

KEY REQUIREMENTS AND TECHNOLOGY EXPERIENCE:

• Key Skills; Python, Docker, Kubernetes, AWS, Azure, SAAS tools
• Proficiency in Python, Bash, or Java.
• Strong understanding of Linux and Windows operating systems.
• In-depth knowledge of networking concepts and distributed systems.
• Hands-on experience with Docker, Kubernetes, and related orchestration tools.
• Familiarity with IaC tools such as Terraform, CloudFormation, or Azure CLI.
• Experience with monitoring and observability platforms.
• Background in incident management, troubleshooting, and systems debugging.
• Experience supporting CI/CD pipelines and version control workflows.
• Excellent problem-solving and communication skills.
• Professional experience with both AWS and Azure cloud platforms.
• Relevant cloud or DevOps certifications (e.g., AWS Certified DevOps Engineer, Azure Solutions Architect).
• Exposure to microservices architecture and AI/ML-based platforms.
• Experience managing large-scale systems and complex infrastructure environments.
  Our client is a leading Healthcare Industry and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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• Build, maintain, and optimize scalable and highly available cloud infrastructure on AWS and Azure.
• Develop and maintain CI/CD pipelines using tools like GitHub and GitHub Actions.
• Implement and manage infrastructure as code (IaC) using tools such as Terraform, CloudFormation, or Azure CLI.
• Monitor and troubleshoot systems using observability tools like New Relic, Azure Monitoring, and Client.
• Containerize applications and manage deployments using Docker and Kubernetes.
• Support and integrate Azure ML, Databricks, and other cloud-based data science tools.
• Lead incident response, perform root cause analysis, and conduct post-incident reviews.
• Automate manual operational processes and contribute to the reliability of services through tooling and scripting in Python, Bash, or Java.
• Ensure high performance, availability, and scalability of infrastructure supporting microservices and AI/ML workloads.
• Create and maintain clear documentation such as runbooks, SOPs, and architecture diagrams.