GenAI Architect

GenAI Architect

Location: Charlotte, NC or Atlanta, GA (Hybrid)
Duration: 12-month contract

Overview

Seeking an experienced GenAI Architect to lead the design, governance, and delivery of enterprise AI/ML solutions for a regulated financial services environment. This role will define platform architecture, AI governance standards, agentic workflows, RAG solutions, and MLOps/LLMOps practices while driving innovation across Azure AI technologies.

Key Responsibilities

• Architect and govern AI platforms leveraging Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, and Azure Storage.
• Design and oversee agentic AI frameworks, AI governance models, access controls, and observability standards.
• Lead RAG architectures, model evaluation, prompt engineering standards, and cost optimization strategies.
• Establish enterprise MLOps/LLMOps practices including model versioning, drift detection, evaluation pipelines, and deployment governance.
• Drive security, compliance, and data governance aligned with financial industry regulations and privacy standards.
• Define long-term AI roadmap, including on-prem/private model hosting, fine-tuning strategies, and model-routing frameworks.
• Mentor engineering teams and conduct architecture reviews.

Required Qualifications

• 10+ years of software engineering and AI/ML systems experience.
• Strong expertise in Azure AI services, cloud architecture, and enterprise-scale AI deployments.
• Proven experience with Agentic AI workflows, RAG, FastAPI, and Pydantic.
• Hands-on experience with MLOps/LLMOps, model training, fine-tuning, and evaluation frameworks.
• Experience implementing AI solutions in regulated financial services environments.
• Strong understanding of AI governance, security, compliance, and observability.

Top 3 Required Skills

• AI/ML Solution Design & Architecture
• Deep Azure Cloud & AI Platform Expertise
• Agentic Workflow Development Experience

Ideal Candidate: A senior AI architect who combines deep Azure expertise with hands-on GenAI, MLOps, governance, and financial-services domain experience to build scalable, secure, production-grade AI platforms.