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AWS engineer at Weekday AI. This role is for one of the Weekday's clients. Min Experience: 2 years. Location: India. JobType: full-time. We are seeking a passionate and results-driven . AWS Engineer. with a strong foundation in . Artificial Intelligence (AI). and cloud infrastructure to join our growing team. As part of our AI initiatives, you will be responsible for designing, developing, deploying, and maintaining scalable cloud-based solutions on AWS. You’ll work closely with data scientists, ML engineers, and software developers to bring AI models into production and optimize the infrastructure supporting intelligent applications.. Key Responsibilities:. . Design and implement robust, secure, and scalable cloud solutions using AWS for AI/ML workloads. . . Deploy and manage AI/ML models using services such as . Amazon SageMaker. , . Lambda. , . ECS/EKS. , and . EC2. . . . Collaborate with AI/ML teams to understand model requirements and translate them into cloud-native architectures. . . Automate cloud infrastructure provisioning and deployment using . Infrastructure as Code (IaC). tools such as . CloudFormation. or . Terraform. . . . Monitor, troubleshoot, and optimize deployed models and pipelines to ensure high performance and reliability. . . Implement CI/CD pipelines tailored for ML workflows, ensuring smooth model training, testing, and deployment cycles. . . Ensure data security and compliance with best practices in managing training datasets and inference endpoints. . . Continuously research and implement the latest AWS tools and best practices related to AI and cloud engineering. . . Key Skills and Qualifications:. . . 2+ years. of hands-on experience working with . AWS cloud services. , particularly in AI/ML contexts. . . Proficiency in AWS services such as . S3. , . EC2. , . Lambda. , . SageMaker. , . IAM. , . CloudWatch. , . ECR. , . ECS. , . EKS. , and . CloudFormation. . . . Familiarity with deploying and maintaining machine learning models in production environments. . . Understanding of core AI/ML concepts, frameworks (such as TensorFlow, PyTorch, or Scikit-learn), and their deployment lifecycle. . . Strong programming/scripting skills in . Python. , . Bash. , or . Node.js. . . . Experience with . Docker. and container orchestration (preferably . Kubernetes. ). . . Exposure to monitoring, logging, and alerting tools like . CloudWatch. , . Prometheus. , or . Grafana. . . . Knowledge of CI/CD practices and tools (e.g., . GitHub Actions. , . Jenkins. , . CodePipeline. ). . . Bachelor’s degree in Computer Science, Engineering, or a related technical field. . . Preferred Qualifications:. . AWS Certification (e.g., . AWS Certified Machine Learning – Specialty. , . Solutions Architect Associate/Professional. ). . . Experience with MLOps frameworks and model versioning tools like . MLflow. or . Kubeflow. . . . Familiarity with data preprocessing pipelines and big data tools like . Apache Spark. , . Glue. , or . Redshift. . . . Experience working in an Agile/Scrum environment.. . Company Location: India.