Agentic AI – AWS Solution Architect (Onsite)

Job Summary

We are looking for strong AI Technical Architect to drive our innovation strategy using Amazon Web Services. This role focuses on building sophisticated, autonomous AI agents using AWS Bedrock. You will be the primary technical authority on Agentic AI, responsible for designing systems where Foundation Models (FMs) interact intelligently with enterprise data and APIs to perform complex tasks. You will lead high-stakes conversations with senior leadership to define the "Art of the Possible" regarding GenAI.

Architecture & Platform Leadership

• Define target architecture, security boundaries, integration patterns, and deployment standards for enterprise Agentic AI and Generative AI solutions.
• Lead architecture reviews covering security, scalability, resiliency, observability, performance, and cost optimization.
• Establish reusable platform patterns, golden-path templates, reference architectures, and production-readiness standards.
• Collaborate with AI engineering, security, cloud, networking, data, and application teams to drive secure and governed adoption of AI capabilities.
• Provide architecture governance, production-readiness oversight, and leadership for security and resiliency reviews.

Agentic AI & AWS AI/ML

• Strong experience architecting and implementing Agentic AI and Generative AI solutions on AWS.
• Hands-on experience with AWS AgentCore, Amazon Bedrock, Amazon SageMaker, and related AWS AI/ML services.
• Experience designing AI agents, multi-agent workflows, LLM-based applications, RAG solutions, tool integration, and model/agent orchestration.
• Design secure integration patterns between AI agents, enterprise applications, APIs, data platforms, knowledge sources, and external tools.
• Experience implementing AI guardrails, security controls, model governance, observability, monitoring, and responsible AI practices.
• Experience taking AI/ML and Generative AI solutions from prototype/PoC through production deployment.
• Design Agentic AI solutions for enterprise-grade scalability, resiliency, security, performance, and operational supportability.

Cloud Engineering & DevSecOps

• Design and manage secure multi-account AWS environments using AWS Organizations, Control Tower, SCPs, IAM Identity Center, and shared services.
• Develop and manage CI/CD pipelines using GitLab, GitHub, or Bitbucket CI/CD and AWS-native deployment services.
• Build, package, and deploy AgentCore and AI workloads as containerized applications using Docker and Amazon ECR.
• Implement Infrastructure as Code (IaC) using AWS CDK and/or Terraform, including automated 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 the AWS Cedar authorization framework.
• Support threat modeling, security reviews, compliance requirements, and production-readiness assessments.
• Ensure model, agent, and tool interactions follow approved governance and security controls, including deny-by-default Cedar policies, guardrails, private connectivity, identity controls, and secure access patterns.