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Ai Aws Architect

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Location:
United States , Parsippany

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

165000.00 USD / Year
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Job Responsibility:

  • Architect and design an end-to-end solution for an AI-driven Retrieval-Augmented system
  • Define and implement the embedding strategy, document chunking methodology, and ranking techniques to ensure high-quality retrieval
  • Evaluate, select, and integrate appropriate Large Language Models (LLMs) using Amazon Bedrock
  • Design and implement a scalable vector database solution (such as OpenSearch, Qdrant, or MongoDB Atlas with vector search)
  • Architect and deploy the cloud infrastructure leveraging AWS services including Amazon Bedrock (LLM), SageMaker, AWS Lambda, and Amazon EKS
  • Establish MLOps best practices by designing CI/CD pipelines for model deployment and managing model registry updates
  • Apply FinOps principles to balance cost and performance, optimizing model size, inference latency, and caching strategies
  • Design secure access controls and implement secrets management using AWS Secrets Manager

Requirements:

  • 10+ years of experience in Software Development & ML engineering, including 4+ years in Solution architecture or AI architecture delivering production-grade systems
  • Strong hands-on expertise in Python (workflow orchestration, model evaluation), Node.js, and experience working with agent-based frameworks such as AutoGen, LangChain, or ADK. Solid knowledge of prompt engineering techniques and tool-calling mechanisms
  • Deep understanding of retrieval-augmented systems, including embeddings, chunking strategies, ranking mechanisms, and Vector databases such as Qdrant and MongoDB Atlas with vector search capabilities
  • Extensive experience in MLOps practices, including CI/CD pipelines for ML models, model registry management, and containerized deployments using Kubernetes
  • Strong cloud expertise in AWS, with hands-on experience in services such as Amazon Bedrock, SageMaker, AWS Lambda, and Amazon EKS
  • Demonstrated experience in implementing Responsible AI practices, security best practices (encryption, secrets management, network isolation), and FinOps strategies for AI workloads, including cost and latency optimization

Additional Information:

Job Posted:
May 04, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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