What are the responsibilities and job description for the AI Platform Engineer with AWS position at USG, Inc.?
Role Title: AI Platform Engineer (AWS – Financial Services)
Location: Charlotte, NC (Hybrid – 3 Days/Week Onsite)
Job Summary
We are seeking an experienced AI Platform Engineer to design, build, and operate secure, scalable AI platforms on AWS within a highly regulated financial services environment. The ideal candidate will have strong expertise in AWS cloud services, Amazon Bedrock, Kubernetes/EKS, Python development, and enterprise-grade platform engineering.
Key Responsibilities
- Design, build, and operate secure and scalable AI platforms on AWS.
- Develop and manage Generative AI solutions using Amazon Bedrock.
- Build and support containerized AI services on Amazon EKS.
- Develop Python-based AI inference and orchestration workloads.
- Implement serverless AI workflows using AWS Lambda and API Gateway.
- Configure secure networking and access controls using VPC, IAM, and private endpoints.
- Integrate AWS services such as S3, DynamoDB, messaging, and streaming platforms to support AI pipelines and RAG architectures.
- Establish CI/CD pipelines, monitoring, logging, and operational controls.
- Collaborate with Security, Architecture, Risk, and Compliance teams to ensure adherence to financial services regulations.
Required Qualifications
- 8 years of Python development experience supporting APIs, AI services, or automation workflows.
- 5 years of experience building cloud platforms on AWS.
- 5 years of experience designing secure, highly available, and scalable distributed systems.
- 5 years of experience working within regulated industries such as Financial Services, Banking, or Insurance.
- 2 years of hands-on experience with:
- Amazon Bedrock
- Amazon EKS / Kubernetes
- AWS Lambda
- AWS Networking Services (VPC, IAM, Private Endpoints)
Education
- Bachelor's Degree in Computer Science, Engineering, or equivalent practical experience.
Preferred Qualifications
- Experience supporting AI/ML or Generative AI platforms in production environments.
- Knowledge of model governance, data security, auditability, and access controls.
- Experience with Infrastructure as Code (Terraform, CloudFormation, or AWS CDK).
- Experience with CI/CD pipelines and enterprise production operations.
Work Model
- Hybrid role requiring onsite presence in Charlotte, NC three days per week.
- Minimal travel required.
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