GenAI Architect

TekCommands; Georgia (AL); Hybrid; USD 190,000 - 270,000; Full time

Job summary

BlackCube Labs in the United States seeks a GenAI Architect to lead the design and governance of enterprise AI/ML solutions within a regulated financial services environment. The role offers a hybrid option in Charlotte, NC or Atlanta, GA.

You will define platform architecture, AI governance standards, agentic workflows, RAG solutions, and MLOps/LLMOps practices while mentoring engineering teams and driving security, privacy, and compliance.

Qualifications

• 10+ years in software and AI/ML systems.
• Strong Azure services and enterprise-scale deployments.
• Experience with regulated financial services environments.
• Knowledge of AI governance, security, and observability.

Responsibilities

• Architect and govern AI platforms using Azure components.
• Design agentic AI frameworks and governance models.
• Lead RAG architectures, prompt engineering, and cost optimization.
• Establish MLOps/LLMOps practices including versioning and drift detection.
• Drive security, compliance, and data governance per regulations.
• Define long-term AI roadmap including on-prem hosting and fine-tuning.
• Mentor teams and conduct architecture reviews.

Skills

AI/ML Architecture

Azure Cloud Expertise

Agentic Workflow Dev

Tools

Azure OpenAI

Azure AI Foundry

Azure Functions

Azure Storage

FastAPI

Pydantic

Job description

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.