Platform Engineer

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