Generative AI Engineer (Remote – United States) This position is posted on behalf of a partner company. The Generative AI Engineer will own the technical delivery and evolution of enterprise AI solutions, ensuring reliability, scalability, security, and continuous improvement. Responsibilities include designing and developing production-grade generative AI systems, including LLM-powered applications, agentic workflows, and retrieval-augmented generation architectures integrated with enterprise data and services. You will establish reusable engineering patterns for prompt management, workflow versioning, structured outputs, tool orchestration, and AI service lifecycle management. You will evaluate model choices, routing strategies, latency, token usage, and cost efficiency, and you will integrate AI solutions with enterprise platforms, APIs, databases, and cloud-native services to create reliable production workflows. You will own operational performance, including monitoring, observability, scalability, and incident response, and you will build and maintain CI/CD pipelines for AI deployment, testing, and release management. You will develop automated evaluation frameworks for LLM outputs, including prompt regression testing, retrieval quality validation, and failure analysis. You will implement responsible AI practices through security controls, human-in-the-loop processes, and structured output validation, and define technical standards and best practices across teams. You will provide technical guidance through architecture reviews, code reviews, mentorship, and collabora

Generative AI Engineer (Remote – United States) This position is posted on behalf of a partner company. The Generative AI Engineer will own the technical delivery and evolution of enterprise AI solutions, ensuring reliability, scalability, security, and continuous improvement. Responsibilities include designing and developing production-grade generative AI systems, including LLM-powered applications, agentic workflows, and retrieval-augmented generation architectures integrated with enterprise data and services. You will establish reusable engineering patterns for prompt management, workflow versioning, structured outputs, tool orchestration, and AI service lifecycle management. You will evaluate model choices, routing strategies, latency, token usage, and cost efficiency, and you will integrate AI solutions with enterprise platforms, APIs, databases, and cloud-native services to create reliable production workflows. You will own operational performance, including monitoring, observability, scalability, and incident response, and you will build and maintain CI/CD pipelines for AI deployment, testing, and release management. You will develop automated evaluation frameworks for LLM outputs, including prompt regression testing, retrieval quality validation, and failure analysis. You will implement responsible AI practices through security controls, human-in-the-loop processes, and structured output validation, and define technical standards and best practices across teams. You will provide technical guidance through architecture reviews, code reviews, mentorship, and collabora