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Niche LLM-plus-cloud skillset reduces applicant pool despite mid-level role attractiveness.
Requires specialized AWS Bedrock and LLM engineering skills, limiting cross-industry transferability.
Explicit 6+ years, 3+ years AWS, and specific LLM/AWS/CI-CD/IaC requirements increase shortlisting strictness.
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Design, develop, and operate scalable, production-grade AI/ML services and applications on AWS.
Build and integrate APIs and AI capabilities including LLM applications, retrieval-augmented generation, and AI agents.
Manage CI/CD pipelines, containerization, infrastructure-as-code, and evaluation pipelines to ensure quality and automated deployment.
6+ years of professional experience in software, data, or AI/ML engineering.
3+ years of hands-on experience building and operating production services on AWS.
Strong proficiency in Python and experience with AWS services such as Lambda, ECR, S3, API Gateway, IAM, CloudWatch.
Experience with CI/CD tools (e.g. GitHub Actions, Jenkins), containerization (Docker), and Infrastructure as Code (AWS CDK, Terraform, CloudFormation).
Hands-on engineer with strong coding and implementation skills in Python, AWS, and Generative AI/LLM applications rather than an architect role.
Experienced in integrating AI agents, RAG, knowledge graphs, and evaluation pipelines for AI applications.
Comfortable working independently within existing complex architectures and collaborating across engineering, AI/ML, and DevOps teams.