AWS AI Architect - Agentic AI & Cloud Engineering

Job Description:

We are seeking a highly experienced AWS AI Architect with 15+ years of overall IT experience and strong expertise in AWS Cloud Engineering, DevOps, cloud security, and Agentic AI platforms.

The primary focus of this role is AWS Cloud Engineering and DevOps, with hands‑on responsibility for designing, deploying, securing, and operating scalable multi‑account AWS environments and production‑grade AI platforms.

The ideal candidate will have extensive experience with AWS architecture, enterprise cloud engineering, CI/CD, Infrastructure as Code, cloud security, AWS Bedrock AgentCore, Strands Framework, MCP integrations, and AI observability.

Key Responsibilities

Cloud Engineering & DevOps – Primary Focus

• Design, build, and maintain secure, scalable multi-account AWS environments.
• Define enterprise-level AWS architecture and cloud engineering standards.
• Develop and manage automated CI/CD pipelines using GitLab CI/CD and AWS-native deployment services.
• Build, package, containerize, and deploy AgentCore workloads using Docker and Amazon ECR.
• Implement Infrastructure as Code using AWS CDK and CDK Pipelines.
• Configure and manage AWS Systems Manager (SSM) for operational automation.
• Design and optimize data persistence solutions using Amazon DynamoDB.
• Implement secure authentication and authorization using OAuth / OBO patterns.
• Apply security and authorization policies using the AWS Cedar Policy Framework.
• Implement AWS Organizations and Service Control Policies (SCPs) for enterprise governance.
• Design secure AWS networking using VPC Endpoints and AWS PrivateLink.
• Monitor, troubleshoot, and optimize cloud workloads and deployment processes.
• Lead production deployments, release management, operational readiness, and incident resolution.
• Establish cloud security, monitoring, logging, resiliency, and operational best practices.

Agentic AI & AgentOps

• Design and implement AI agents and multi-agent orchestration workflows using the Strands Framework.
• Build and operate solutions using AWS Bedrock AgentCore Runtime and AgentCore Gateway.
• Support AgentOps and platform operations, including AgentCore Runtime, Agent Registry, MCP integrations, OTEL, and operational monitoring.
• Develop and manage MCP (Model Context Protocol) integrations with enterprise systems and applications.
• Integrate AWS Bedrock Foundation Models with enterprise applications and APIs.
• Implement AI observability, governance, security, monitoring, and distributed tracing.
• Optimize AI agent performance, scalability, reliability, and cost efficiency in production environments.

Architecture & Technical Leadership

• Provide technical leadership for enterprise AWS and Agentic AI initiatives.
• Lead architecture and design reviews for complex cloud-native platforms.
• Define technical standards, reusable patterns, and best practices for AWS engineering and DevOps.
• Mentor senior engineers and provide technical direction across cloud, DevOps, and AI engineering teams.
• Collaborate with security, application, data, DevOps, and AI teams to deliver enterprise solutions.
• Evaluate emerging AWS and AI technologies and recommend appropriate solutions for enterprise adoption.

Required Qualifications

• 15+ years of overall IT / software engineering experience.
• Extensive experience in AWS Cloud Architecture and Engineering.
• Strong experience designing and implementing enterprise-scale cloud-native solutions.
• Extensive hands‑on experience with DevOps, CI/CD, and Infrastructure as Code.
• Strong experience with GitLab CI/CD, Docker, Amazon ECR, AWS CDK, and CDK Pipelines.
• Experience with AWS Organizations, SCPs, IAM Identity Center, VPC Endpoints, and PrivateLink.
• Strong knowledge of CloudWatch, CloudTrail, OpenTelemetry (OTEL), and cloud monitoring.
• Experience with AWS Systems Manager (SSM) and DynamoDB.
• Strong understanding of cloud security, governance, authentication, and authorization.
• Experience with OAuth / OBO authentication patterns.
• Experience with the AWS Cedar Policy Framework.
• Strong Python and cloud-native application development experience.
• Hands‑on experience with Agentic AI / Generative AI platforms.
• Experience with AWS Bedrock AgentCore Runtime and Gateway, Strands Framework, and MCP integrations.

Preferred Qualifications

• AWS Certified Solutions Architect or AWS Certified DevOps Engineer.
• Experience building and operating enterprise-scale Agentic AI platforms.
• Strong experience with event-driven architectures and microservices.
• Experience with AI governance, security, observability, and responsible AI practices.
• Experience leading complex cloud modernization and enterprise platform initiatives.

Nice-to-Have Skills

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