AWS Architect

Job Summary

We are looking for a highly skilled and hands-on AWS Solutions Architect to design and implement end-to-end cloud solutions using AWS native services. The ideal candidate will have strong expertise in architecting scalable, secure, and cost-efficient solutions across data, serverless, and AI/ML domains.

This role requires deep solutioning capability using AWS services such as SageMaker, Glue, RDS, S3, Lambda, API Gateway, OpenSearch, and Amazon Bedrock, with the ability to assist DevOps engineers when needed. The candidate will collaborate closely with data scientists, engineering teams, and business stakeholders to deliver robust cloud-native architectures.

Key Responsibilities

• Design and implement end-to-end AWS cloud solutions using native AWS services.
  

• Architect and deploy data pipelines and analytics solutions using AWS Glue, S3, RDS, and OpenSearch.
  

• Build and support AI/ML workflows using Amazon SageMaker.
  

• Assist data science teams in building knowledge bases and GenAI solutions using Amazon Bedrock.
  

• Design and implement serverless architectures using AWS Lambda, API Gateway, Step Functions, and related services.
  

• Ensure high availability, scalability, security, and cost optimization across solutions.
  

• Provide architectural guidance and best practices to development and DevOps teams.
  

• Assist DevOps engineers with CI/CD, infrastructure automation, and cloud deployment strategies when required.
  

• Conduct architecture reviews and recommend improvements aligned with AWS Well-Architected Framework.
  

• Stay updated with new AWS services and emerging cloud technologies.
  

Required Skills & Experience

Core AWS Expertise

• Strong hands-on experience with:
  

  • Amazon S3
    

  • AWS Lambda
    

  • API Gateway
    

  • AWS Glue
    

  • Amazon RDS
    

  • Amazon OpenSearch
    

  • Amazon SageMaker
    

  • Amazon Bedrock
    

• Experience designing serverless and event-driven architectures.
  

• Strong understanding of AWS IAM, networking (VPC, subnets, security groups), and cloud security best practices.
  

Data & AI Experience

• Experience building data ingestion and ETL pipelines.
  

• Understanding of ML model lifecycle and deployment.
  

• Exposure to GenAI and knowledge base creation using Bedrock or similar services.
  

DevOps Knowledge (Support Level)

• Familiarity with CI/CD pipelines (CodePipeline, GitHub Actions, Jenkins, etc.).
  

• Infrastructure as Code (CloudFormation/Terraform – basic to intermediate level).
  

• Containerization knowledge (ECS/EKS/Docker) is a plus.