Principal AWS Gen-AI Architect – Agentic AI

Role: Principal AWS Gen-AI Architect – Agentic AI

Location: Remote

We are seeking a highly experienced Principal Gen-AI Architect to design and lead enterprise-scale Generative AI and Agentic AI platforms. This role requires deep AWS architecture expertise, strong knowledge of modern AI orchestration frameworks built using Python on LangChain/similar, and the ability to communicate effectively with both technical teams and executive stakeholders.

Key Responsibilities

Architect enterprise-scale Generative AI and Agentic AI platforms on AWS.

Design scalable solutions leveraging Amazon Bedrock, EKS, ECR, Fargate, and AWS X-Ray.

Define architecture for RAG, contextual retrieval, AI agents, orchestration, and MCP server integrations.

Establish platform standards for security, governance, Responsible AI, observability, and regulatory compliance.

Design cloud agnostic containerized AI solutions capable of supporting enterprise-scale deployments.

Provide technical leadership for AI application development, integration, and deployment.

Lead architecture reviews and technical design discussions with engineering teams, customers, and executive stakeholders.

Evaluate emerging AI technologies, frameworks, and architectural patterns for enterprise adoption.

Required Qualifications

12+ years of overall software engineering, architecture, or technology leadership experience, including significant experience designing AI/ML and cloud-based solutions.

Strong hands-on architecture experience with AWS, particularly Gen-AI/ML and cloud-native platforms.

Proven experience designing enterprise Generative AI or Agentic AI solutions.

Strong experience with Amazon Bedrock preferably with Kubernetes/EKS.

Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies.

Strong understanding of RAG, contextual information retrieval, AI agents, and LLM-based application architecture.

Experience designing and deploying containerized solutions using technologies such as EKS, ECR, Fargate, and Docker.

Strong understanding of AI security, governance, Responsible AI, and enterprise architecture standards.

Excellent communication and presentation skills with experience working directly with customers and senior/executive stakeholders.

Strong development background in Python; .NET or Java experience also considered.

Preferred Qualifications

Experience with evaluation frameworks (Evals) for Generative AI/LLM applications.

Experience integrating MCP servers or similar AI tool/integration architectures.

Experience with Helm Charts and CI/CD for Kubernetes-based deployments.

Experience designing cloud-agnostic or multi-cloud architectures, particularly across AWS and Azure.

Experience within healthcare, life sciences, BFSI, GRC, or other highly regulated industries.

Familiarity with data contracts, data-access governance, and enterprise data-sharing patterns.

Experience developing or implementing enterprise AI accelerator frameworks or automation platforms.

AWS AI/ML or AWS Solutions Architect certification is a plus.