Data Engineer (Platform)

R SYSTEMS CONSULTING SERVICES LIMITED; Singapore; Presencial; SGD 120.000 - 180.000; Jornada completa

Descripción de la vacante

R SYSTEMS CONSULTING SERVICES LIMITED is seeking a platform engineer to design, implement, and operate AWS-based infrastructure to support Amazon Bedrock and AgentCore workloads. You will build scalable, secure cloud components and enable reliable AI agent deployments in production.

You will work with IAM, VPC, Lambda, ECS/EKS, CloudWatch, S3, and other services; develop IaC with Terraform, CloudFormation, or CDK; and implement CI/CD pipelines while ensuring governance, monitoring, and cost

Formación

• Extensive hands-on AWS cloud infrastructure and platform engineering experience.
• Knowledge of IAM, VPC, networking, security, identity and observability.
• Familiar with Bedrock and Bedrock AgentCore platform configuration.
• Experience with IaC tools: Terraform, CloudFormation, or CDK.

Responsabilidades

• Design, configure, and manage AWS platform components to support Bedrock and AgentCore workloads.
• Establish scalable, secure, and reliable cloud infrastructure for AI agent apps.
• Implement IaC with Terraform, CloudFormation, or CDK.
• Set up CI/CD pipelines and automated deployment processes for platform components.
• Establish monitoring, logging, tracing, and alerting for production workloads.
• Collaborate with AI developers, architects, security, and DevOps to provide reusable platform capabilities.
• Troubleshoot infrastructure, permissions, networking, and deployment issues.
• Define platform standards, templates, guardrails, and best practices.

Conocimientos

AWS platform engineering

Security & IAM best practices

CI/CD implementation

Networking & VPC design

Platform observability

Herramientas

Terraform

AWS CloudFormation

AWS CDK

Docker

ECS/EKS

Descripción del empleo

Key Responsibilities

• Design, configure, and manage AWS platform components required to support Amazon Bedrock and AgentCore workloads.
• Establish and maintain scalable, secure, and reliable cloud infrastructure for AI agent applications.
• Work with AWS services such as IAM, VPC, networking, AWS Lambda, Amazon ECS/EKS, CloudWatch, S3, and other relevant platform services.
• Configure and manage Amazon Bedrock and AgentCore capabilities from a platform and infrastructure perspective.
• Implement platform-level security, identity and access management, authentication, authorization, secrets management, and network controls.
• Enable agent deployment, runtime management, environment configuration, connectivity, and operational support.
• Build and maintain Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, or AWS CDK.
• Implement CI/CD pipelines and automated deployment processes for platform components and agent-based applications.
• Establish monitoring, logging, tracing, alerting, troubleshooting, and operational practices for production workloads.
• Optimize platform performance, scalability, availability, reliability, and cost.
• Collaborate with AI application developers, solution architects, security teams, and DevOps engineers to provide reusable platform capabilities and deployment standards.
• Troubleshoot infrastructure, permissions, networking, runtime, integration, and deployment issues across AWS environments.
• Define platform standards, reusable templates, guardrails, and best practices for teams developing AI-powered applications.

Required Skills and Experience

• Strong hands-on experience with AWS cloud infrastructure and platform engineering.
• Good understanding of AWS architecture, including compute, storage, networking, security, identity, and observability.
• Working knowledge of Amazon Bedrock, including its platform configuration, access management, service integration, and operational considerations.
• Hands-on knowledge of Amazon Bedrock AgentCore, particularly runtime deployment, identity, gateway, observability, and related platform capabilities.
• Strong understanding of IAM roles and policies, least-privilege access, VPC networking, security groups, endpoints, and secrets management.
• Experience with Infrastructure as Code tools such as Terraform, CloudFormation, or AWS CDK.
• Experience with CI/CD pipelines, automated deployments, and environment management.
• Knowledge of containers and serverless technologies, such as Docker, ECS/EKS, and AWS Lambda.
• Experience with platform monitoring, logging, troubleshooting, and production support.
• Understanding of enterprise cloud platform design, including security, governance, scalability, reliability, and cost management.