Senior AWS Cloud & Generative AI Engineer Job at Purple Drive, Atlanta, GA

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  • Purple Drive
  • Atlanta, GA

Job Description

Key Responsibilities:

  • Design, develop, and implement Generative AI solutions leveraging Amazon Bedrock and related AWS services.
  • Configure and optimize Amazon Bedrock Agent Orchestration for intelligent workflow and model lifecycle management.
  • Apply Prompt Engineering methodologies for fine-tuning and optimizing AI model outputs.
  • Implement Amazon Bedrock Guardrails to ensure compliance, brand safety, and responsible AI governance.
  • Integrate and manage Amazon Knowledge Bases and Vector Databases to enhance contextual understanding and retrieval-augmented generation (RAG) workflows.
  • Employ MLOps practices to automate model training, deployment, and monitoring within enterprise environments.
  • Build and maintain CI/CD pipelines to support scalable and efficient deployment of AI and cloud-native applications.
  • Utilize AWS services including CloudFormation, CDK, Step Functions, Lambda, EventBridge, DynamoDB, S3, Glue, and Athena to design and orchestrate robust cloud infrastructures.
  • Develop infrastructure as code (IaC) solutions using AWS CDK and CloudFormation , ensuring version control and repeatable deployments.
  • Collaborate with data scientists, solution architects, and DevOps teams to integrate AI capabilities with existing business systems.
  • Create and maintain comprehensive technical documentation , including runbooks, design documents, and troubleshooting guides for deployed solutions.
  • Ensure all solutions meet AWS best practices for security, compliance, scalability, and cost optimization .
Required Skills & Experience:

  • 10+ years of hands-on experience in AWS Cloud Computing within enterprise environments.
  • Proven experience with Amazon Bedrock , including agent orchestration, workflow management, and model fine-tuning.
  • Strong knowledge of Generative AI architectures , LLM integration, and Prompt Engineering techniques.
  • Expertise in AWS Cloud Development Kit (CDK) , CloudFormation , and Infrastructure as Code (IaC) principles.
  • Proficiency with AWS services such as S3, Lambda, EventBridge, DynamoDB, Glue, Step Functions, and Athena.
  • Experience implementing MLOps pipelines using AWS-native tools and frameworks.
  • Solid understanding of CI/CD pipeline automation using AWS or third-party tools (e.g., CodePipeline, Jenkins, GitHub Actions).
  • Familiarity with security and compliance standards for AI and cloud environments.
  • Strong problem-solving, analytical, and communication skills, with a proven ability to work collaboratively across technical and non-technical teams.
Preferred Qualifications:

  • AWS Certified Solutions Architect / DevOps Engineer / Machine Learning Specialty certification.
  • Experience deploying Retrieval-Augmented Generation (RAG) systems using AWS Bedrock and vector search technologies.
  • Prior experience integrating LLMs (e.g., Anthropic Claude, Amazon Titan, or other Bedrock models) into enterprise solutions.
  • Working knowledge of Python, TypeScript, or Java for automation and API integration.

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