AI & Infrastructure Engineer ISKT-001
Posted
Summary
An AI & Infrastructure Engineer (3–5 yrs) who deploys and manages AI/ML models on AWS. Day to day: building AI applications and agents in Python (LangGraph, AgentCore), maintaining Docker containers, EC2/S3/Lambda/VPC infrastructure, CI/CD pipelines, monitoring performance and cloud costs, and handling security, backup and troubleshooting.
AI & Infrastructure Engineer
Experience: 3–5 Years of experience
Location: Singapore
Key Responsibilities
- Deploy and manage AI/ML models in cloud environments.
- Develop AI applications using Python.
- Build AI agents using LangGraph and AgentCore Runtime.
- Set up and maintain AWS infrastructure, including EC2, S3, Lambda, IAM and VPC.
- Build and manage Docker containers for AI applications.
- Develop and maintain CI/CD pipelines for automated deployment.
- Monitor application performance, infrastructure health and cloud costs.
- Implement security, access control, backup and recovery practices.
- Troubleshoot AI application and infrastructure issues.
- Work with development teams to support AI model integration and production deployment.
Required Skills
- 3–5 years of experience in AI/ML engineering, cloud infrastructure or DevOps, Python development and AI engineering
- Hands-on experience with LLMs, AI agents and LangGraph.
- Hands-on experience with AWS services such as EC2, S3, Lambda, IAM and VPC.
- Experience with Docker and container deployment.
- Knowledge of Python and Linux.
- Experience deploying AI/ML models and integrating APIs.
- Familiarity with CI/CD tools such as Jenkins or GitHub Actions.
- Knowledge of monitoring, logging, networking and cloud security.
Good to Have
- Experience with Amazon SageMaker or AWS Bedrock.
- Knowledge of Kubernetes and infrastructure as code using Terraform or CloudFormation.
- Experience with GPU-based AI model deployment.
- Familiarity with LLMs and generative AI applications.