Cloud AI engineer

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 (GenAI) technologies. The ideal candidate will have 68 years of hands-on experience in building robust data platforms, deploying scalable ML models, and integrating GenAI solutions across cloud environments.

• Design and implement production-ready GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI
• Develop and deploy AI/ML models, including transformer-based and LLM (Large Language Model) solutions
• Integrate GenAI 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 GenAI capabilities
• Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments
• Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI 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 GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI
• Develop and deploy AI/ML models, including transformer-based and LLM (Large Language Model) solutions
• Integrate GenAI 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 GenAI capabilities
• Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments
• Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI 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