Python Engineer with Aws Bedrock

Hi Professionals We are looking for a Python Engineer having experience in aws and bedrock for one of my client

We are seeking a skilled Python Developer with AWS and Amazon Bedrock experience to design and build scalable Generative AI solutions. This role will focus on developing cloud-native applications, integrating Large Language Models (LLMs), and implementing secure, production-grade AI services within AWS environments.

The ideal candidate has strong backend development expertise, hands-on experience with AWS services, and practical experience building AI-driven applications using Amazon Bedrock or similar LLM platforms.

Key Responsibilities

• Design, develop, and maintain Python-based backend applications.

• Build and integrate Generative AI solutions using Amazon Web Services services, including Amazon Bedrock.

• Implement LLM integrations, prompt engineering, and AI workflow orchestration.

• Develop and deploy microservices in AWS environments.

• Work with AWS services such as Lambda, API Gateway, S3, EC2, IAM, and CloudWatch.

• Build RESTful APIs and event-driven architectures.

• Ensure security best practices (IAM roles, encryption, secrets management).

• Optimize application performance, scalability, and reliability.

• Collaborate with data scientists, DevOps, and product teams.

• Participate in CI/CD pipeline development and deployment automation.

Required Qualifications

• 4+ years of experience in Python development.

• Strong hands-on experience with AWS cloud services.

• Experience working with Amazon Bedrock or other LLM platforms.

• Solid understanding of REST APIs and microservices architecture.

• Experience with cloud-native application development.

• Familiarity with version control (Git) and CI/CD pipelines.

• Strong debugging and problem-solving skills.

Preferred Qualifications

• Experience with LLM frameworks (e.g., LangChain).

• Knowledge of embeddings, vector databases, or prompt engineering.

• Experience with Docker and Kubernetes.

• Familiarity with AWS SageMaker or other AI services.

• Understanding of secure AI deployment and governance.

• AWS certifications (e.g., AWS Developer Associate, AWS Solutions Architect).