GenAI DevOps Engineer /AI Engineer

BlackCube Labs; Los Angeles (CA); On-site; USD 150,000 - 185,000; Full time

Job summary

BlackCube Labs is seeking a GenAI DevOps Engineer / AI Engineer in Los Angeles to design, deploy, and optimize intelligent AI agents using Claude Agent SDK and Amazon Bedrock. You will build production-grade agent workflows and automate CI/CD in a cloud-native setup.

Proficiency in Python or TypeScript, plus strong AWS experience (Bedrock, ECR, IAM, CloudWatch) is required, along with Terraform/AWS CDK for IaC.

Qualifications

• 6–10 years of experience in DevOps, cloud engineering, or AI/ML infrastructure.
• Proficiency in Python and/or TypeScript for agent development and automation.
• Strong hands-on experience with AWS services including Bedrock, ECR, IAM, CloudWatch, and VPC configuration.
• Demonstrated expertise with CI/CD tools, particularly GitHub Actions, and infrastructure-as-code (Terraform or AWS CDK).
• Solid understanding of containerization, Docker, and container orchestration.
• Experience with AI/ML concepts including prompt engineering, tool calling, model calling patterns, and agent frameworks.
• Knowledge of security best practices, authentication mechanisms, and cloud infrastructure hardening.
• Excellent troubleshooting and problem‑solving skills with a focus on production reliability and monitoring.

Responsibilities

• Design, develop, and implement AI agents using the Claude Agent SDK and Amazon Bedrock AgentCore Runtime
• Build agent workflows in Python or TypeScript, including tool calling, MCP integrations, and API orchestration
• Develop and maintain automated CI/CD pipelines using GitHub Actions for agent builds, testing, and deployments
• Configure and manage AWS infrastructure including IAM policies, ECR registries, Docker containerization, and cloud security best practices
• Monitor, troubleshoot, and optimize production AI agent performance using CloudWatch and observability tools
• Implement secure authentication, logging, and monitoring for agent systems to ensure compliance and visibility
• Collaborate with cross-functional teams to integrate AI agents into broader application architectures

Skills

Python

TypeScript

AWS services

CI/CD concepts

Security best practices

Tools

GitHub Actions

Terraform

AWS CDK

Docker

ECR

Job description

Our client is seeking a GenAI DevOps Engineer / AI Engineer to design, develop, and deploy intelligent AI agents using Claude Agent SDK and Amazon Bedrock, building production-grade agent workflows and implementing CI/CD automation in a cloud-native environment.

Responsibilities & Qualifications

• Design, develop, and implement AI agents using the Claude Agent SDK and Amazon Bedrock AgentCore Runtime
• Build agent workflows in Python or TypeScript, including tool calling, MCP integrations, and API orchestration
• Develop and maintain automated CI/CD pipelines using GitHub Actions for agent builds, testing, and deployments
• Configure and manage AWS infrastructure including IAM policies, ECR registries, Docker containerization, and cloud security best practices
• Monitor, troubleshoot, and optimize production AI agent performance using CloudWatch and observability tools
• Implement secure authentication, logging, and monitoring for agent systems to ensure compliance and visibility
• Collaborate with cross-functional teams to integrate AI agents into broader application architectures

Requirements

• 6–10 years of experience in DevOps, cloud engineering, or AI/ML infrastructure
• Proficiency in Python and/or TypeScript for agent development and automation
• Strong hands‑on experience with AWS services including Bedrock, ECR, IAM, CloudWatch, and VPC configuration
• Demonstrated expertise with CI/CD tools, particularly GitHub Actions, and infrastructure-as-code (Terraform or AWS CDK)
• Solid understanding of containerization, Docker, and container orchestration
• Experience with AI/ML concepts including prompt engineering, tool calling, model calling patterns, and agent frameworks
• Knowledge of security best practices, authentication mechanisms, and cloud infrastructure hardening
• Excellent troubleshooting and problem‑solving skills with a focus on production reliability and monitoring