GenAI Platform Engineer: Scalable AI/LLMOps

SMBC; Charlotte (NC); Hybrid; USD 130,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

SMBC is seeking an experienced Staff AI/GenAI Engineer to design, develop, and deploy scalable AI platforms within the Platform Engineering team. You will collaborate with architecture, data, and business units and partner with Azure, Databricks, and other infrastructure providers to deliver enterprise-grade GenAI capabilities.

This role requires hands-on coding, fast learning of new GenAI tech, and governance for secure, compliant GenAI solutions in a financial services environment.

Qualifications

• Bachelor’s degree in Computer Science, Machine Learning, Data Science, or related field.
• 3+ years of hands-on GenAI or advanced ML models in production.
• 3+ years of Python and GenAI frameworks/tools (e.g., Databricks Vector Search, Azure AI, LangGraph, haystack, Llama Index).
• Strong knowledge of prompt engineering, embedding models, and RAG implementations.

Responsibilities

• Define AI Platform architecture using Databricks and Azure Cloud Services.
• Develop platform infra and REST/Websocket-based AI services for downstream apps.
• Own MLOps/LLMOps for model lifecycle management, observability, and security.
• Data engineering to support AI/ML data requirements.
• Build and maintain GenAI workflows with RAG and Agentic orchestration layers.
• Evaluate emerging GenAI tech and integrate those with business value.
• Mentor engineering teams on GenAI techniques and platform capabilities.

Skills

Python

GenAI frameworks

Databricks

Azure

MLOps

REST APIs

CI/CD

Containerization

PyTorch

TensorFlow

Education

Bachelors degree in CS/ML/Data Science

Tools

MLflow

LangGraph

Haystack

Llama Index

Databricks

Job description

SMBC is seeking an experienced Staff AI/GenAI Engineer to design, develop, and deploy scalable AI platforms within the Platform Engineering team. You will collaborate with architecture, data, and business units and partner with Azure, Databricks, and other infrastructure providers to deliver enterprise-grade GenAI capabilities.

This role requires hands-on coding, fast learning of new GenAI tech, and governance for secure, compliant GenAI solutions in a financial services environment.