What you will be doing
Continuous Integration/Continuous Delivery (CI/CD): Design, build, and maintain robust CI/CD pipelines to automate the build, test, and deployment of applications for both the ReactJS front end and back-end services.
Infrastructure as Code (IaC): Use tools like Terraform to provision and manage AWS resources, including EC2, S3, Lambda, EKS/ECS, and RDS.
Containerization and Orchestration: Manage containerized applications using Docker and orchestrate them with Amazon Elastic Kubernetes Service (EKS) or Amazon Elastic Container Service (ECS).
AWS Environment Management: Deploy, manage, and maintain the AWS cloud infrastructure, ensuring high availability, performance, and cost efficiency.
MLOps Platform Support: Collaborate with data scientists and MLOps team to build and maintain the infrastructure that supports the end-to-end machine learning lifecycle, including model development, training, deployment, monitoring, and retraining.
Data Platform Operations: Automate data pipelines and manage the Snowflake environment, ensuring data governance, quality, and security.
Monitoring and Logging: Implement and manage monitoring, logging, and alerting systems to ensure the health, performance, and security of all applications and infrastructure.
Security: Enforce security best practices, implement access controls (IAM), and ensure compliance across the entire cloud and platform stack.
About You
·10+ years of experience with DevOps engineering and cloud-based solutions.
Proven experience as a DevOps Engineer, with a focus on AWS cloud services.
Proficiency with Infrastructure as Code (IaC) tools such as Terraform. Good to understand AWS CloudFormation.
Experience with CI/CD tools: GitHub CI/CD and GitHub Actions.
Strong scripting skills in Python, Bash, ReactJS and Shell.
Knowledge of the complete software development lifecycle and Agile methodologies.
Hands-on experience with containerization using Docker and orchestration with Kubernetes (EKS) or ECS.
Nice to have
Data warehousing on Snowflake and integrating it with cloud environments.
Understanding of MLOps concepts and experience supporting machine learning pipelines is a plus.
Excellent problem-solving, communication, and collaboration skills.
DevOps certifications are preferred.
Experience in healthcare or life sciences domain is a plus.
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