AI Platform Engineer (AWS - Financial Services)

Usg Inc.

Charlotte, NC, United States

5 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

2 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Audit Trail Continuous Integration Data as a Services Data Security Distributed Systems Amazon DynamoDB Identity and Access Management Python (Programming Language)

+15 more

Network Security Systems Integration Data Logging AWS Lambda Amazon Virtual Private Cloud (VPC) Cloudformation Event Driven Architecture AI Platforms Kubernetes Information Technology Machine Learning Operations Api Gateway Terraform Automation Anywhere Serverless Computing

Job description

Design, build, and operate secure, scalable AI platforms on AWS for enterprise and regulated environments
Develop and manage generative AI solutions using Amazon Bedrock for model integration and deployment
Build and operate containerized AI services on Amazon EKS supporting Python-based inference and orchestration workloads
Develop serverless AI workflows using AWS Lambda, API Gateway, and event-driven architectures
Implement secure networking and access controls using VPC, IAM, and private endpoints
Integrate data services such as S3, DynamoDB, and messaging/streaming platforms to enable AI pipelines and RAG architectures
Establish CI/CD, monitoring, logging, and operational controls aligned to enterprise and regulatory standards
Collaborate with security, architecture, and risk teams to ensure compliance with financial services requirements

Requirements

5+ years building cloud platforms on AWS
2+ years hands-on with Amazon Bedrock, EKS/Kubernetes, AWS Lambda, and core AWS networking services
8+ years of Python development supporting APIs, AI services, or automation workflows
5+ years designing secure, highly available, distributed systems at scale
5+ years working in regulated environments (financial services, banking, or insurance)

Nice to Have:

Experience supporting AI/ML or generative AI platforms in production
Knowledge of data security, model governance, auditability, and access controls
Experience with Infrastructure as Code (Terraform, CloudFormation, or CDK)
Exposure to CI/CD pipelines and production operations in enterprise environments

Degree: Bachelor’s in Computer Science, Engineering, or equivalent work experience

Travel: Minimal; 3 days/week in client office, ability to support stakeholders as needed