AWS AI Platform Engineer (MCP Experience Required)
About The Position
AWS AI Platform Engineer (MCP Experience Required) We are looking to hire a candidate with the skills sets mentioned and experience for one of our clients within the pharmaceutical Industry. Job Summary We are seeking a Senior AWS Platform Engineer / AWS AI Infrastructure Engineer to design, deploy, and support scalable, secure cloud platforms on AWS. The ideal candidate will have hands-on experience with AWS AI services (Bedrock, SageMaker) , containerized deployments ( ECS, EKS, Fargate ), and AWS infrastructure management in production environments. This role will focus on hosting and managing MCP servers , enforcing security best practices, automating cloud operations, and supporting platform reliability. You will collaborate closely with application, DevOps, and engineering teams to ensure high availability, performance, and compliance across AWS environments.
Requirements
- 5-7 years of hands-on AWS experience with medium-level depth across core services.
- Strong familiarity with AWS AI Infrastructure, including Amazon Bedrock and SageMaker .
- Proven experience designing and managing MCP Servers in AWS.
- Hands-on experience with Docker-based deployments using ECS, EKS, and Fargate.
- Solid experience with AWS EC2 configuration, hardening, and security.
- Experience working with AWS databases (RDS, DynamoDB, Aurora, or hosted databases on EC2).
- Strong understanding of AWS IAM, security protocols, roles, policies, and access controls.
- Experience configuring and securing API Gatewa y access.
- Hands-on experience with DevOps practices, automation, and CI/CD pipelines in AWS.
- Experience providing AWS platform administration and production support.
- Familiarity with monitoring, logging, and alerting using AWS-native tools.
- Ability to work collaboratively with application, DevOps, and platform teams.
Responsibilities
- Design, host, manage, and support AWS-based AI and application infrastructure in production environments.
- Architect and manage MCP Servers hosted on AWS, ensuring scalability, availability, and security.
- Deploy and manage containerized workloads using Docker on ECS, EKS, and Fargate.
- Support and administer core AWS infrastructure including EC2, networking, and security configurations.
- Work with AWS AI services, including Amazon Bedrock and Amazon SageMaker, to support AI/ML workloads.
- Manage and support AWS databases (both managed and self-hosted) for application and AI use cases.
- Implement and maintain DevOps practices, CI/CD pipelines, and infrastructure automation in AWS.
- Configure and manage API Gateway, including secure access, integrations, and authorization.
- Ensure AWS environments follow best practices for security, IAM roles and policies, scalability, and reliability.
- Monitor, troubleshoot, and resolve production issues across AWS platforms.
- Provide AWS platform administration and ongoing support.
- Document system architectures, deployment processes, runbooks, and operational procedures.
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What This Job Offers
Career Level
Mid Level
Education Level
No Education Listed
