Applied AI Architect

Brillio

. Design target architectures and scalable data pipelines for enterprise AI systems .

Posted 10/4/2026full-timeRemote • New York • United StatesMid-LevelSenior💰 $150,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable AI solutions, integrating with enterprise systems while ensuring compliance with governance and security standards. Proficient in MLOps, CI/CD, and model lifecycle management within regulated environments.

Highest-signal resume keywords

AI Architecture DesignGenerative AI UnderstandingAzure AI Foundry ExperienceAI Governance and ComplianceMLOps and CI/CD Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Solutions DesignData Pipeline ArchitectureETL/ELT DevelopmentModel Evaluation and SelectionEnterprise Data ArchitectureAI Model Risk ManagementProduction AI EngineeringData Residency ManagementSecurity and Privacy ControlsRegulatory Compliance

Soft Skills

Strong Communication Skills

Tools & Technologies

AWS BedrockGoogle Vertex AILangGraphLangChainEHR IntegrationCRM Platform IntegrationData Lake IntegrationData Warehouse Integration

Industry Keywords

HIPAAGxP/CSVAMLBasel IIISR 11-7PHI GovernancePII GovernanceIAMAccess ControlModel Inference Security

Tech Stack

Tools & technologies

AWSAzureETL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Great Place to Work® recognition
Opportunity to work with cutting-edge technologies
Opportunity to solve complex, high-impact business challenges