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Brillio is a technology consulting company helping organizations navigate digital transformation across healthcare, insurance, logistics, financial services, telecom and media, life sciences, and retail. Its work spans customer experience, data and AI, generative AI, product and platform engineering, and infrastructure, cloud, and security. Brillio combines engineering expertise with industry knowledge to develop digital products and modernize technology environments, helping businesses respond to changing market and technology demands.
Applied AI Architect - Brillio (Remote, New York)
Design governed, scalable AI platforms for Brillio’s enterprise technology clients. Integrate data, cloud infrastructure, security, and production machine learning systems.
United States
New York$150,000 – $250,000 / year
RemoteFull-timeMiddleSeniorEnglish RequiredAI EngineerMachine Learning EngineerDescription
- Develop reference architectures and scalable data pipelines for enterprise AI platforms
- Design ETL/ELT workflows, feature stores, vector databases, knowledge layers, and AI data pipelines
- Assess AI models against use-case fit, performance, cost, latency, security, and governance criteria
- Architect AI integrations with EHRs, core banking platforms, CRM systems, data lakes, and data warehouses
- Create and apply frameworks for AI governance, compliance, privacy, and responsible AI
- Convert regulatory obligations into practical technical controls and architecture decisions
- Incorporate security, privacy, identity and access management, and data residency requirements
- Design production deployments using Azure AI Foundry, AWS Bedrock, and Google Vertex AI
- Collaborate with AI Builders and Value Engineers throughout discovery, design, and production delivery
- Build the foundations for MLOps, CI/CD, model lifecycle management, observability, monitoring, and evaluation
- Advance AI initiatives from proof of concept to secure, scalable production deployment
Requirements
- Demonstrated experience as an AI, machine learning, data, solutions, or enterprise architect, including hands-on AI solution delivery
- Strong command of generative AI, agentic AI, retrieval-augmented generation, AI orchestration, and contemporary AI architectures
- Background in enterprise data architecture, pipeline design, system integration, and scalable AI platform development
- Experience comparing AI models and balancing commercial versus open-source options, as well as RAG versus fine-tuning
- Practical experience with Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, and LangChain
- Experience connecting AI solutions to enterprise systems and APIs
- Deep understanding of AI governance, model risk management, responsible AI, privacy, security, and regulatory compliance
- Experience in regulated industries; familiarity with HIPAA, GxP/CSV, AML, Basel III, or SR 11-7 is highly desirable
- Experience governing PHI and PII, data residency, VPC deployments, IAM, access controls, and model inference security
- Experience delivering production AI systems with CI/CD, MLOps, model registries, monitoring, observability, and evaluation frameworks
- Clear communicator who can turn complex technical, business, security, and regulatory needs into sound architecture decisions
Benefits
- Recognition as a Great Place to Work®
- Access to current and emerging technology work
- The chance to address complex, high-impact business problems
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