Applied AI Architect
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Job Description
Applied AI Architect designing governed, scalable AI platforms for Brillio’s Fortune 1000 digital technology clients. Integrating enterprise data, cloud, security, and production ML systems.
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 integrating with 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
- Design production environments across Azure AI Foundry, AWS Bedrock, and Google Vertex AI
- Partner with AI Builders and Value Engineers from discovery through production
- Establish foundations for MLOps, CI/CD, model lifecycle management, observability, monitoring, and evaluation
- 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 tradeoffs between commercial and open-source models, and RAG versus fine-tuning
- Experience with 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; exposure to HIPAA, GxP/CSV, AML, Basel III, or SR 11-7 highly desirable
- Experience with 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 ability to translate complex technical, business, security, and regulatory requirements into clear architectural decisions
Benefits:
- Great Place to Work® recognition
- Opportunity to work with cutting-edge technologies
- Opportunity to solve complex, high-impact business challenges
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