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Niche MCP/LLM platform skills reduce applicants, but common devops and Python/AWS requirements keep competition moderate.
High - specialized MCP and LLM platform operational experience limits transferable candidate pools across industries.
High - explicit 6+ years plus specific MCP, Python, AWS, observability and IaC requirements.
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Design, build, deploy, and maintain scalable AI platform services primarily using Python and AWS cloud-native technologies.
Manage MCP Server Management and Observability for AI-powered applications, including monitoring, logging, and tracing of MCP-based services.
Develop and support LLM-based application workflows, containerized workloads, CI/CD pipelines, and infrastructure-as-code implementations.
6+ years of professional experience in software, data, or AI/ML engineering.
3+ years of experience building and operating production services on AWS.
Proficiency in MCP Server Management, MCP Observability, and Python.
Experience with AWS CloudFormation and operational tools like Amazon CloudWatch.
Experienced in managing and operating MCP implementations specifically for AI applications and ecosystem integrations.
Comfortable working with cloud-native AWS architecture and infrastructure-as-code tooling such as AWS CDK or Terraform.
Capable of independently understanding complex AI platform architectures and driving continuous service improvements.