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GenAI DevOps Engineer /AI Engineer - Remote/Hybrid with Travel

Job Description - GenAI DevOps Engineer /AI Engineer - Remote/Hybrid with Travel



Senior GenAI DevOps Engineer /AI Engineer - Remote/Hybrid with Travel






The key is time zone coverage and so we can expand our search across the West Coast - remote/hybrid but necessarily located in the western time zones. You must be comfortable to travel to the client site for workshops/meetings. 







 



 



  1. Senior GenAI DevOps Engineer /AI Engineer  who has 10-15+ years overall experience and 6-8 years building AI agents and deploying them into production on AWS.



The role combines AI agent development (60%) and DevOps/CI/CD engineering (40%). This is a suggested split based on the responsibilities you've described.


Job Description – AI Agent Engineer (Claude SDK / AWS AgentCore / GitHub Actions)


Experience: 10-15+ years overall, including hands-on GenAI or agentic AI development.


Key responsibilities



  • Design, develop, and implement AI agents using the Claude Agent SDK (formerly Claude Code SDK).


  • Build agent workflows using Python or TypeScript, including tool calling, MCP integrations, and API orchestration.


  • Deploy and manage AI agents on Amazon Bedrock AgentCore Runtime.


  • Develop automated CI/CD pipelines using GitHub Actions for agent builds, testing, and deployments.


  • Configure AWS IAM, ECR, Docker/container packaging where applicable, and cloud security.


  • Monitor, troubleshoot, and optimize production AI agent performance.


  • Implement secure authentication, logging, monitoring, and observability.



Skills to look for
























































Skill



Priority



What to verify



Claude Agent SDK



Must-have



Hands-on agent development, not just Claude prompting



Amazon Bedrock AgentCore Runtime



Must-have



Actual agent deployment and runtime configuration



GitHub Actions



Must-have



Building CI/CD pipelines independently



Python or TypeScript



Must-have



Strong coding and API integration



AWS Bedrock



Must-have



Model integration and AWS ecosystem knowledge



Docker, AWS ECR, IAM



Strongly preferred



Packaging, deployment, permissions



MCP and tool calling



Strongly preferred



Building agents that execute external tools



Terraform / AWS CDK



Good-to-have



Infrastructure as Code



CloudWatch, security, monitoring



Good-to-have



Production support



 













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