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Mid-level, popular ML/AI title with employer recognition but niche LLM/AWS specialization.
Specialized LLM, AWS, and AI infrastructure requirements limit cross-industry transferability.
Explicit 6+ years and mandatory LLM, AWS, Python, CI/CD, containerization, and IaC skills.
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Design, develop, and operate scalable AI/ML production services on AWS with Python and containerization.
Build and integrate APIs and AI/LLM-powered applications including retrieval-augmented generation, prompt orchestration, and AI agents.
Develop and maintain CI/CD pipelines, infrastructure-as-code, and evaluation pipelines for AI application quality improvement.
6+ years of professional experience in software, data, or AI/ML engineering.
3+ years hands-on building and operating production services on AWS (Amazon Bedrock, Lambda, S3, ECR, API Gateway, IAM, CloudWatch).
Strong proficiency in Python with solid software engineering fundamentals (testing, code reviews, version control).
Experience with CI/CD tools (GitHub Actions, Jenkins) and Infrastructure-as-Code (AWS CDK, Terraform, CloudFormation).
Hands-on engineer with strong coding and implementation skills across Python, AWS, Generative AI/LLM, APIs, DevOps, and cloud-native services.
Experience with AI frameworks such as Model Context Protocol (MCP), Bedrock AgentCore, retrieval-augmented generation, and knowledge graphs.
Able to understand and contribute independently within existing architectures and complex codebases.