[Hiring] AWS AI Architect @Centraprise

Role Description

We are seeking a highly experienced AWS AI Architect with strong expertise in Cloud Engineering, DevOps, and Agentic AI platforms on AWS. The ideal candidate will have hands-on experience building and deploying scalable cloud-native solutions, automated CI/CD pipelines, and production-grade AI agent systems leveraging AWS Bedrock AgentCore, MCP integrations, and the Strands framework. Cloud engineering and DevOps capabilities are the primary focus of this role.

Key Responsibilities:

• Cloud Engineering & DevOps (Primary)
• Design, build, and maintain secure, scalable, multi-account AWS environments
• Develop and manage CI/CD pipelines using GitLab CI/CD and AWS-native deployment services
• Build, package, and deploy AgentCore workloads as containerized applications using Docker and Amazon ECR
• Implement Infrastructure as Code (IaC) using AWS CDK and automated CDK deployment pipelines
• Configure and manage AWS Systems Manager (SSM) for operational automation
• Design and optimize data persistence using Amazon DynamoDB
• Implement secure authentication and authorization using OAuth/OBO patterns
• Apply security and governance policies using AWS Cedar authorization framework
• Support SCP-based governance controls and production security policies
• Monitor, troubleshoot, and optimize cloud workloads and deployment processes
• AI Engineering - Agentic AI and AgentOps
• Build AI agents and multi-agent orchestration workflows using the Strands Framework with AWS Bedrock AgentCore Runtime & Gateway
• Experience in AgentOps and Platform operations for AgentCore runtime, Agent registry, MCP integration, OTEL, Ops. Monitoring
• Implement AI observability, operational monitoring, and distributed tracing
• Develop and manage MCP (Model Context Protocol) integrations with enterprise systems and tools
• Integrate Bedrock foundation models with enterprise applications and APIs
• Implement AI observability, governance, security, and runtime monitoring
• Optimize AI agent performance, scalability, and cost efficiency in production environments

Qualifications

• Cloud Engineering / DevOps (Mandatory & Critical)
• AWS Cloud Architecture and Engineering
• GitLab CI/CD
• Docker & Amazon ECR
• AWS Organizations / SCPs
• CloudWatch + OTEL + CloudTrail
• AWS CDK & CDK Pipelines
• AWS Systems Manager (SSM)
• Amazon DynamoDB
• IAM Identity Center
• VPC Endpoints / PrivateLink
• Cedar Policy Framework
• OAuth / OBO Authentication
• Infrastructure as Code (IaC)
• Cloud Security & Monitoring
• Production Deployment & Release Management
• Agentic AI / Generative AI
• AWS Bedrock AgentCore Runtime
• AWS Bedrock AgentCore Gateway
• MCP (Model Context Protocol) Integrations
• Strands Framework
• Agent-based Architecture & Orchestration
• Generative AI & LLM Solutions
• REST APIs & Microservices Integration

Preferred Qualifications

• AWS Certified Solutions Architect / AWS DevOps Engineer Certification
• Experience building enterprise-scale Agentic AI platforms
• Strong expertise in Python and cloud-native application development
• Experience with event-driven architectures and microservices
• Exposure to AI governance, security, and responsible AI practices

Nice to Have

• LangGraph / LangChain exposure
• AWS Bedrock Knowledge Bases
• Amazon API Gateway
• AWS Lambda, Step Functions
• Vector databases and RAG architectures
• Kubernetes / EKS