AWS AI Solution Architect
XCUTIVES Inc.
Sayreville, 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
Job source
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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