We are seeking an experienced engineer to support the development and delivery of Generative AI platform capabilities across hybrid infrastructure environments. This role focuses on building scalable AI/ML platforms and supporting model delivery across both on-premises infrastructure and cloud platforms including GCP Vertex AI and Azure ML. The ideal candidate has strong experience in LLM, Generative AI development/operations, MLOps, Python, and large-scale data platforms, along with the ability to design resilient, high-performance infrastructure supporting AI and NLP workloads. Key Responsibilities Participate in the development and expansion of Generative AI platform capabilities supporting enterprise AI initiatives Deliver and operationalize AI models to on-prem infrastructure and cloud platforms (GCP Vertex AI, Azure ML) Participate in daily standups and Agile development cycles supporting platform capability development Research industry best practices, evaluate emerging technologies, and define engineering standards and automation strategies to improve platform resiliency and reliability Execute technology roadmaps aligned with business and engineering strategy Perform hardware capacity planning, performance analysis, and forecasting to ensure scalability and high availability of AI/ML workloads Support infrastructure designed for high-throughput, low-latency AI and NLP workloads Serve as a technical subject matter expert and collaborate with engineering teams across the organization Minimum Requirements 2+ years of experience with LLMs and Generative AI (development, operations, or platform engineering) 5+ years of Python development experience 5+ years of experience with big data technologies such as BigQuery or Hadoop 5+ years of Linux systems experience 3+ years of experience in AI/ML and MLOps environments 3+ years of PySpark experience 3+ years of VMware virtualization experience Experience working with AutoML technologies such as H2O Driverless AI, DataRobot, Vertex AI, Elastic, and Vector databases Experience designing and supporting grid computing environments with CPU and GPU resources for AI/ML and NLP workloads Working knowledge of high-performance storage systems and object storage Strong understanding of network infrastructure supporting high-throughput, low-latency compute environments Excellent communication skills with the ability to present technical solutions to both technical and business audiences Demonstrated ability to influence technical and business decisions Preferred Skills Experience developing APIs on GCP, Azure, or API Gateway platforms Experience with Elasticsearch, Vector databases, or AI model development Experience with enterprise data processing platforms such as AbInitio, Informatica, or IBM DataStage Experience working with large data ecosystems including Hadoop, Teradata, and Elasticsearch Familiarity with Agile development methodologies and working within Agile teams Experience implementing load balancing technologies such as F5 Experience designing high-resiliency cloud or grid computing environments supporting AI/ML workloads Knowledge of cloud computing, PaaS architectures, microservices, and containerized environments