GenAI Devops Engineer - AWS Bedrock

*****GenAI DevOps Engineer AWS Bedrock*****

*****Pune Hinjewadi*****

*****Immediate Joiners Preferred*****

*****Minimum 4 Days WFO*****

We are seeking a highly experienced GenAI DevOps Engineer to join our dynamic team in Pune. The ideal candidate will have a strong background in building, deploying, and optimizing Generative AI applications on AWS Bedrock, along with expertise in DevOps practices. You will be responsible for automating infrastructure, managing CI/CD pipelines, and ensuring high performance and reliability of AI models.

Key Responsibilities:

Design, develop, and deploy Generative AI applications leveraging AWS Bedrock and SageMaker.

• Automate infrastructure provisioning and deployment processes.
• Build and maintain robust CI/CD pipelines using CodePipeline and CodeBuild.
• Monitor application and model performance using CloudWatch, Prometheus, and Grafana.
• Optimize AI models for performance, scalability, and cost-efficiency.
• Work with RAG (Retrieval-Augmented Generation) tools such as LangChain, Haystack, and LlamaIndex for building advanced AI solutions.
• Collaborate with data scientists and developers to streamline model deployment and monitoring.

Required Skills:

• Extensive hands-on experience with AWS Bedrock and SageMaker.
• Strong expertise in CI/CD tools: CodePipeline, CodeBuild.
• Proficiency with monitoring tools: CloudWatch, Prometheus, Grafana.
• Experience with RAG frameworks like LangChain, Haystack, and LlamaIndex.
• Solid understanding of DevOps best practices and automation.
• Ability to troubleshoot and optimize AI deployment pipelines.
• Excellent problem-solving and communication skills.

Preferred Skills:

• Knowledge of containerization (Docker, Kubernetes).
• Familiarity with scripting languages (Python, Bash).
• Experience with cloud security best practices.
• Understanding of machine learning lifecycle management.

Mandatory Skills:

• AWS Bedrock and SageMaker expertise.
• CI/CD pipeline automation.
• Monitoring and performance optimization.
• RAG-based application development.