AWS AI Solution Architect

XCUTIVES Inc.
South Plainfield, NJ, United States
11 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Cloud Engineering Continuous Integration Information Engineering DevOps Distributed Systems Amazon DynamoDB Python (Programming Language) Retrieval-Augmented Generation
+14 more
Multi-Agent Systems Generative AI AWS Lambda Agentic-AI Event Driven Architecture Data Lakes Kubernetes Infrastructure Automation Frameworks Amazon Bedrock AWS Glue Api Gateway Serverless Computing Amazon Redshift Microservices

Job description

  • Architect and implement AWS-native AI solutions using Amazon Bedrock, AWS Lambda, Amazon ECS/EKS, SageMaker, API Gateway, S3, Glue, Redshift, DynamoDB, and related AWS services.
  • Design Agentic AI and RAG-based solutions, including AI orchestration, tool integration, security guardrails, and enterprise-scale deployment patterns.
  • Define cloud architecture standards, microservices patterns, serverless designs, integration approaches, observability, resiliency, and governance frameworks.
  • Lead customer workshops, solution design sessions, architecture reviews, and guide engineering teams through implementation.

Requirements

Role Overview: We are seeking a hands-on AWS Solution Architect with 8-12 years of experience in designing and delivering cloud-native, AI-powered enterprise solutions. The ideal candidate will bring strong expertise in AWS Cloud, Generative AI, Agentic AI, application modernization, and scalable distributed architectures, with the ability to translate business requirements into secure, resilient, and production-ready solutions., * AWS Cloud Architecture, Amazon Bedrock, Generative AI, Agentic AI, RAG, Python, and solution design.

  • Microservices, serverless computing, containers, Kubernetes/EKS, API-led integration, and event-driven architecture.
  • Data engineering, data lakes, AWS Glue, Redshift, DynamoDB, CI/CD, DevOps, Infrastructure as Code, and observability.
  • Strong customer-facing communication, consulting mindset, technical leadership, and ability to align business outcomes with AWS architecture.

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