Cloud engineer

4 weeks ago

Bangalore, India People Prime Worldwide Full time

Job Description: We are looking for an experienced Cloud AI and Data Engineer with a strong background in cloud-native data solutions, AI/ML engineering, and emerging Generative AI (Gen AI) technologies. The ideal candidate will have 6–8 years of hands-on experience in building robust data platforms, deploying scalable ML models, and integrating Gen AI solutions across cloud environments. · Design and implement production-ready Gen AI applications using services like Amazon Bedrock, Azure Open AI, or Google Vertex AI · Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions · Integrate Gen AI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns · Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and Gen AI capabilities · Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for Gen AI deployments · Set up monitoring, drift detection, and governance mechanisms for both traditional and Gen AI models · Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.g., AWS Glue, Azure Data Factory, GCP Dataflow)· Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies · Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards · Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.g., AWS Glue, Azure Data Factory, GCP Dataflow)· Design and implement production-ready Gen AI applications using services like Amazon Bedrock, Azure Open AI, or Google Vertex AI · Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions · Integrate Gen AI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns · Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and Gen AI capabilities · Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for Gen AI deployments · Set up monitoring, drift detection, and governance mechanisms for both traditional and Gen AI models · Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies · Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards

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