AI Engineer

Design, implement, and manage cloud infrastructure on AWS using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation. Maintain and enhance CI/CD pipelines using tools like GitHub Actions, AWS CodePipeline, Jenkins, or ArgoCD. Ensure platform reliability, scalability, and high availability across development, staging, and production environments. Automate operational tasks, environment provisioning, and deployments using scripting languages such as Python, Bash, or PowerShell. Enable and maintain Amazon SageMaker environments for scalable ML model training, hosting, and pipelines. Integrate AWS Bedrock to provide foundation model access for generative AI applications, ensuring security and cost control. Manage and publish curated infrastructure templates through AWS Service Catalogue to enable consistent and compliant provisioning. Collaborate with security and compliance teams to implement best practices around IAM, encryption, logging, monitoring, and cost optimization. Implement and manage observability tools like Amazon CloudWatch, Prometheus/Grafana, or ELK for monitoring and alerting. Support container orchestration environments using EKS (Kubernetes), ECS, or Fargate. Contribute to incident response, post-mortems, and continuous improvement of the platform operational excellence. Required Skills & Qualifications: Bachelors degree in Computer Science, Engineering, or related field (or equivalent experience). 5plus years of hands on experience with AWS cloud services. Strong experience with Terraform, AWS CDK, or CloudFormation. Proficiency in Linux system administration and networking fundamentals. Solid understanding of IAM policies, VPC design, security groups, and encryption. Experience with Docker and container orchestration using Kubernetes (EKS preferred). Hands-on experience with CI/CD tools and version control (Git). Experience with monitoring, logging, and alerting systems. Strong troubleshooting skills and ability to work independently or in a team. Preferred Qualifications (Nice to Have): AWS Certification (e.g., AWS Certified DevOps Engineer, Solutions Architect Associate/Professional). Experience with serverless technologies like AWS Lambda, Step Functions, and EventBridge. Experience supporting machine learning or big data workloads on AWS.