Senior AWS AI/ML Solutions Architect

Job Title- Senior AWS AI/ML Solutions Architect

Work Location & Reporting Address

Irvine CA 92618 ( onsite - 5 days a week)

Vendor Rate

$55/hr

Contract duration

6 Months

Interview Process -Virtual

Must Have Skills

Strong hands-on experience with AWS cloud architecture and infrastructure.

Experience with Amazon Bedrock and Generative AI/LLM-based solution architecture.

Understanding of Model Context Protocol (MCP) and MCP server deployment/integration.

Strong knowledge of AWS IAM, VPC, CloudWatch, CloudTrail, Secrets Manager, and AWS security practices.

Domain

Food And Beverage

Nice to have skills

Proficiency with key AWS services such as IAM, VPC, CloudWatch, CloudTrail, and Secrets Manager.

Detailed Job Description

Responsible for designing and supporting the AWS environment, including MCP server setup and configuration of the Amazon Bedrock foundation to enable secure and scalable AI solutions.Key Responsibilities Design and support a secure, scalable, and resilient AWS cloud environment for the solution. Set up and configure the MCP server, including secure connectivity with applications, APIs, and enterprise systems. Establish and configure the Amazon Bedrock foundation, including model access, permissions, and application integration. Implement AWS security and networking using IAM, VPC, security groups, encryption, and secrets management. Support monitoring, troubleshooting, performance, and cost Eligible to workimization of the AWS environment.Key Skills Strong experience in AWS cloud architecture, infrastructure, networking, and security. Handson experience with Amazon Bedrock and Generative AILLM architectures. Understanding of Model Context Protocol MCP and MCP server deploymentintegration. Proficiency with key AWS services such as IAM, VPC, CloudWatch, CloudTrail, and Secrets Manager.

Minimum years of experience

15 years

Certifications Needed

Yes

Relevant AWS certifications needed

Top 3 responsibilities you would expect the Subcon to shoulder and execute

Design and support a secure, scalable, and resilient AWS cloud environment for the solution.

Set up and configure the MCP server, including secure connectivity with applications, APIs, and enterprise systems.

Establish and configure the Amazon Bedrock foundation, including model access, permissions, and application integration.