Senior AWS Cloud & Generative AI Engineer
Purple Drive
Overview: 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 .
- 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.
- 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.
Vacancy posted 1 day ago
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