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AWS Data & AI Platform Engineer

VDart, Inc.Charlotte, NC🇺🇸United StatesPosted 31 Jul 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Job Title: AWS Data & AI Platform Engineer

Location: Charlotte, NC (Hybrid)

Type: Contract

Job Description – AI Platform Engineer (AWS – Financial Services)

Day to Day job Duties:

  • 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

Basic Qualifications:

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

Travel:

  • Minimal travel required; ability to support client stakeholders in regulated environments as needed.  3 days per week in client office.

Degree:

  • Bachelor’s degree in Computer Science, Engineering, or equivalent work experience
  • Nice to Have; (But not a must)
  • 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

Skills

DynamoDB
API Gateway
AWS
CDK
CloudFormation
Generative AI
Kubernetes
Python
Terraform

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