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Specialized LLM role at a known global firm creates moderate competitive density.
AI/LLM and cloud engineering skills are transferable across industries but require specific LLM experience.
Many mandatory technical skills (LLMs, AWS, Terraform, databases, Java/Python) imply strict filters.
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Develop AI/ML solutions using Python, Core JAVA/J2EE, and work extensively with Large Language Models (LLMs) and Generative AI frameworks such as LangChain, Llama Index, or custom Retrieval-Augmented Generation architectures.
Build and deploy AI applications within the AWS ecosystem utilizing services like AgentCore, Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3.
Implement and maintain RESTful web services, continuous integration/delivery pipelines, and manage databases (Oracle 11 or SQL Server) and infrastructure-as-code using Terraform.
Proficiency in Python and Core JAVA/J2EE development.
Experience with Large Language Models (LLMs) and Generative AI frameworks (LangChain, Llama Index, custom RAG).
Hands-on experience with AWS services related to AI solutions including SageMaker, Lambda, API Gateway, and S3.
Knowledge of RESTful web services, database experience (Oracle 11 or SQL Server), Terraform, and cloud/container platforms like AWS ECS.
Experienced in scalable, distributed high-traffic web services using REST API frameworks.
Strong background in AI/ML solution development combined with practical deployment on AWS.
Familiarity with both backend development (Java, Python) and frontend/web technologies including JavaScript frameworks (NodeJS, Angular).