Applied AI Architect - R01572122
About The Position
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. 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.
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.
- 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.
Nice To Haves
- Healthcare experience with FHIR/HL7, Epic, or Oracle is a plus
- Financial services experience with payment data and core banking platforms is a plus
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
Benefits
- Recognized year after year as a Great Place to Work®
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
