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Remote role with mid-level experience and in-demand GenAI skills increases competition.
Requires deep GenAI and AWS Bedrock expertise, limiting transferability across non-AWS environments.
Explicit 5+ years, 3+ years AWS, and mandatory Bedrock/SageMaker skills imply strict technical filters.
Design and develop generative AI applications leveraging Amazon Bedrock, Bedrock AgentCore, and foundation models.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Bedrock Knowledge Bases with features like agentic retrieval and multi-modal content support.
Develop, fine-tune, and deploy custom ML models using SageMaker; implement prompt engineering workflows and manage Bedrock Guardrails for content safety and compliance.
Bachelor's degree in Computer Science, Data Science, AI/ML, or related field.
Minimum 5 years software or ML engineering experience, including 3+ years hands-on with AWS AI/ML services.
Proficiency in building GenAI applications using Amazon Bedrock and SageMaker, including experience with RAG pipelines and orchestration frameworks like LangChain or LlamaIndex.
Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
Experienced in end-to-end GenAI application development within AWS ecosystem, including advanced prompt engineering and compliance configuration.
Skilled at integrating multimodal AI capabilities and orchestration frameworks for production use cases.
Capable of guiding junior engineers and articulating technical decisions in AI/ML development contexts.