Applied AI Architect - R01572122

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.

About 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.

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

Requirements

• Strong experience as an AI, ML, Data, Solutions, or Enterprise Architect, with hands-on experience designing and deploying AI solutions.
• Strong understanding of Generative AI, Agentic AI, RAG, AI orchestration, and modern AI architectures.
• Experience designing enterprise data architectures, pipelines, integrations, and scalable AI platforms.
• Experience evaluating AI models and understanding the tradeoffs between commercial and open-source models, as well as RAG versus fine-tuning.
• Experience with platforms and frameworks such as Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, and LangChain.
• Experience integrating AI with enterprise systems and APIs.
• Healthcare experience with FHIR/HL7, Epic, or Oracle is a plus, as is financial services experience with payment data and core banking platforms.
• Strong understanding of AI governance, model risk management, responsible AI, privacy, security, and regulatory compliance.
• Experience working within regulated environments, with exposure to requirements such as HIPAA, GxP/CSV, AML, Basel III, or SR 11-7 highly desirable.
• Experience with enterprise security concepts including PHI/PII governance, data residency, VPC deployment, IAM, access control, and model inference security.
• Experience with production AI engineering, including CI/CD, MLOps, model registries, monitoring, observability, and evaluation frameworks.
• Strong communication skills and the ability to translate complex technical, business, security, and regulatory requirements into clear architectural decisions.