Staff AI Engineer

JCW Group; Charlotte (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

JCW Group is seeking a hands-on AI Platform Engineer to join a leading global banking organization in Charlotte, NC. You will help shape enterprise-scale GenAI platforms, automation agents, and reusable AI services that enable AI adoption across the business.

The role requires experience building production-grade AI products, strong backend and cloud infrastructure skills, and a track record of delivering scalable AI systems in fast-moving environments.

Qualifications

• Experience shipping production AI/GenAI products.
• Strong knowledge of Azure and Databricks.
• Familiar with LangGraph, LlamaIndex, or similar.

Responsibilities

• Build scalable AI/GenAI platform services and infrastructure.
• Develop AI-powered applications, automation agents, and enterprise AI workflows.
• Build RAG pipelines, vector search capabilities, and orchestration frameworks.
• Develop backend services and APIs using Python.
• Implement LLMOps/ MLOps best practices including monitoring, evaluation, observability, and guardrails.
• Design scalable solutions capable of supporting enterprise-wide adoption.
• Contribute to architecture, technical standards, and platform engineering best practices.

Skills

GenAI platforms

Python backend

Azure

Databricks

RAG architectures

LLMOps tooling

Observability

Cloud infrastructure

Enterprise systems

Vector databases

Job description

Our client, a leading global banking organisation, is building a next-generation AI Platform Engineering function responsible for delivering scalable AI capabilities across the business.

This is a rare opportunity to join a high-calibre engineering team at the early stages of a major enterprise AI transformation. The team is building cutting-edge GenAI platforms, automation agents, and reusable AI services that will underpin AI adoption across the organisation.

Working within a highly innovative, greenfield environment, you will help shape the architecture, tooling, and engineering standards behind enterprise-scale AI systems in a business-critical setting.

The successful candidate will be a highly hands-on engineer with strong experience building production-grade AI products and scalable cloud-based systems.

Key Responsibilities

• Build scalable AI/GenAI platform services and infrastructure
• Develop AI-powered applications, automation agents, and enterprise AI workflows
• Build RAG pipelines, vector search capabilities, and orchestration frameworks
• Develop backend services and APIs using Python
• Implement LLMOps/MLOps best practices including monitoring, evaluation, observability, and guardrails
• Design scalable solutions capable of supporting enterprise-wide adoption
• Contribute to architecture, technical standards, and platform engineering best practices

Required Experience

• Experience building and deploying AI/GenAI products in production environments
• Strong knowledge of Azure and Databricks
• Experience with RAG architectures, embeddings, vector databases, and prompt engineering
• Experience with AI orchestration frameworks such as LangGraph, LlamaIndex, or similar
• Strong backend engineering and cloud infrastructure experience
• Experience building scalable enterprise-grade systems
• Comfortable operating in fast-moving, greenfield environments
• MLflow / LLMOps tooling
• AI observability and evaluation tooling
• Customer-facing AI products or chatbots
• Financial services or regulated environment experience