AWS (Python & Generative AI)

Job Summary:

The AWS (Python & Generative AI) Engineer will design, develop, and deploy cloud-native and AI-driven solutions using AWS and Python. This role focuses on building Generative AI applications leveraging LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and AWS Bedrock services to support intelligent, scalable business solutions.

Location:

Malvern, PA

Experience:

6-8 Years

Key Responsibilities:

• Design and develop AWS-based applications using Python

• Build and deploy Generative AI solutions using Large Language Models (LLMs)

• Implement prompt engineering strategies for optimized AI responses

• Design and implement Retrieval-Augmented Generation (RAG) architectures

• Work with AWS Bedrock and Agent Core for AI model integration and orchestration

• Integrate AI solutions with data sources and analytics platforms

• Ensure scalability, security, and performance of cloud applications

• Collaborate with business and technical teams to translate requirements into solutions

• Troubleshoot, optimize, and enhance existing AWS and AI solutions

• Develop and maintain technical documentation and best practices

Required Skills & Experience:

• 6-8 years of hands-on experience in AWS cloud development

• Strong programming experience in Python

• Solid knowledge of AWS services and cloud architecture

• Hands-on experience with LLMs and Generative AI concepts

• Experience with prompt engineering and RAG frameworks

• Practical experience with AWS Bedrock and Agent Core

• Understanding of cloud security and performance optimization

Competencies:

• Strong analytical and problem-solving skills

• Ability to work independently and collaboratively

• Excellent communication and stakeholder management skills

• Adaptability in a fast-paced, evolving technical environment

• Strong ownership and delivery focus

Preferred Skills:

• Experience with Power BI or other analytics/visualization tools

• Exposure to AI/ML frameworks and data pipelines

• CI/CD and DevOps experience

• Knowledge of MLOps and model lifecycle management