Applied AI Architect - R01572122

Applied AI Architect (Data, Systems & Governance) | Brillio

Architect the Foundations of Enterprise AI

Brillio is looking for an Applied AI Architect who can turn ambitious AI strategies into secure, scalable, enterprise-ready systems.

You'll help determine how AI solutions should be designed, what models should power them, how enterprise data should flow through them, and how they can operate safely within highly regulated environments.

About Brillio

Brillio is one of the fastest-growing digital technology service providers, helping Fortune 1000 organizations turn disruption into competitive advantage through innovative digital adoption.

Our professionals combine deep technology expertise, design thinking, and a strong commitment to client success to deliver transformative outcomes.

Brillio is recognized year after year as a Great Place to Work®

, giving talented technology professionals the opportunity to work with cutting-edge technologies and solve complex, high-impact business challenges.

The Role

As an Applied AI Architect, you'll own the technical foundations that make enterprise AI possible.

You'll bring together data architecture, AI/ML systems, cloud platforms, enterprise integration, security, privacy, and governance to design solutions that can move beyond experimentation and into production.

Role Responsibilities:

• Design target architectures and scalable data pipelines for enterprise AI systems
• Architect ETL/ELT, feature stores, vector databases, knowledge layers, and AI data pipelines
• Evaluate and select AI models based on use case, performance, cost, latency, security, and governance requirements
• Design AI solutions that integrate with enterprise platforms including EHRs, core banking systems, CRM platforms, data lakes, and data warehouses
• Define and implement AI governance, compliance, privacy, and responsible AI frameworks
• Translate regulatory requirements into concrete technical and architectural controls
• Embed security, privacy, IAM, and data residency requirements from day one
• Design production environments across platforms such as Azure AI Foundry, AWS Bedrock, and Google Vertex AI
• Partner closely with AI Builders and Value Engineers throughout the lifecycle — from discovery through production
• Establish the foundations for MLOps, CI/CD, model lifecycle management, observability, monitoring, and evaluation
• Help move AI solutions from proof-of-concept into secure, scalable production environments

Job Requirements:

Strong experience as an AI, ML, Data, Solutions, or Enterprise Architect, with hands-on experience designing and deploying AI solutions.