Job Description:Summary of the AI ArchitectThe AI Architect owns the enterprise AI architecture, standards, and governance for healthcare-grade solutions-establishing reference patterns, platforms, and guardrails that product teams use to safely and efficiently deliver LLM applications, RAG systems, and ML services. This role partners with Security/Compliance, Data/Platform, and Product leaders to ensure HIPAA-aligned handling of PHI/PII, Responsible AI practices, and measurable clinical and business outcomes. The ideal candidate brings deep Azure experience (including Azure AI Foundry / Azure AI Studio), broad knowledge of OpenAI or Anthropic models, and proven enterprise architecture leadership.
This position is remote and based in the United States. The salary range is $150,000 - $200,000, DOE. Employment visa sponsorship is not available for this role.
Responsibilities of the AI ArchitectEnterprise Architecture & Standards- Define and maintain reference architectures for LLM applications, RAG patterns, classical ML, and AI-enabled services across the organization.
- Establish solution blueprints for embeddings/vector search, prompt orchestration, guardrails/safety layers, evaluation frameworks, lineage, and observability.
- Publish SLO/SLA templates, token/GPU budget rules, multi-tenancy/isolation approaches, and cost governance playbooks.
Platform & Tooling- Own platform and tooling selection for Azure AI (Azure AI Foundry/Studio, Azure OpenAI, Azure AI Search, Azure ML), Databricks (Delta Lake, MLflow), and orchestration (Airflow or Azure Data Factory).
- Define standard patterns for vector databases (e.g., Azure AI Search, Pinecone, FAISS), feature store usage, and data ingestion/streaming.
- Provide reference implementations and reusable accelerators (RAG starter kit, evaluation harness, prompt library, safety policies).
Security, Compliance & Responsible AI- Embed PHI/PII safeguards and HIPAA-aligned controls into SDLC and CI/CD gates; standardize data boundaries, de-identification/anonymization (e.g., Presidio), Key Vault, encryption, RBAC, and auditability.
- Define and operationalize Responsible AI requirements (bias/fairness evaluations, model cards, data sheets, red-teaming) as release criteria.
- Partner with Security/Compliance on risk assessments, release approvals, and policy updates; review high-risk use cases
Solution Governance & Reviews- Lead the AI Architecture Review process; manage deviations from standards with an exception register and migration plans.
- Advise squads on prompt design, tool/function calling, grounding/RAG strategies, evaluation design (hallucination, safety, utility), and observability (latency, accuracy, drift, cost).
Collaboration & Enablement- Collaborate with Lead AI Software Engineers, data scientists, and platform teams to land architectures in production.
- Mentor teams in Azure AI Foundry, OpenAI/Anthropic model usage, Microsoft Copilot, and GitHub Copilot-including governance and data leakage prevention.
- Run communities of practice, internal training, and publish architecture decision records (ADRs) and technical standards.
Education and Experience Requirements for the AI Architect- Bachelor's degree in Computer Science, Information Technology, Computer Information Systems, Health Informatics, or a related field.
- 10+ years in software/solution architecture with 5+ years in AI/ML systems and 2+ years leading enterprise AI architecture or platform initiatives.
- Enterprise cloud architecture (Azure): Azure AI Foundry (Azure AI Studio), Azure OpenAI, Azure AI Search, Azure ML, Azure Key Vault, networking/IAM, encryption, logging/monitoring.
- Hands-on architectural experience with OpenAI or Anthropic models (e.g., GPT-4.x/4o, Claude 3.x): prompt & tool calling patterns, grounding/RAG, evaluation methodologies.
- Demonstrated Responsible AI leadership: guardrails, safety filters, bias/fairness evaluations, model cards/datasheets, and red-teaming processes.
- Security & privacy familiarity: PHI/PII protections and HIPAA-aligned design patterns; ability to translate policy into technical controls and CI/CD checks.
- Data platform fluency: Databricks (Delta Lake, MLflow), Spark, orchestration (Airflow or Azure Data Factory/Synapse), and data governance (e.g., Purview).
- MLOps standards: model registry, CI/CD for ML, environment isolation, canary/A/B testing, drift/performance/cost monitoring, rollback strategies.
- Strong understanding of SQL Server data modeling and performance; able to guide teams using SSMS and review T-SQL patterns for AI data workloads.
- Familiarity with Visual Studio and .NET integration patterns to ensure AI services fit the enterprise application ecosystem.
- Experience enabling secure, governed use of Microsoft Copilot and GitHub Copilot in engineering workflows.
- Excellent communication and influence skills; proven success leading architecture reviews and driving cross-functional decisions.
Preferred Education and Experience Requirements for the AI Architect- Healthcare domain knowledge (clinical or revenue cycle management): FHIR/HL7, EHR/claims data integration, and clinical NLP (entity extraction, summarization, coding/RCM use cases).
- Inference optimization: GPU/CUDA, quantization/distillation, caching strategies, prompt/token budgeting, multi-tenant cost control.
- Security/compliance certifications (e.g., HCISPP, CISSP) or demonstrable leadership in healthcare-grade architectures.
- Track record of creating reusable accelerators/libraries/platform capabilities adopted across multiple teams.
- Governance & ethics: model cards, datasheets for datasets, bias/fairness evaluations, and red-teaming.
- Familiarity with .NET microservices and API design to integrate AI services into enterprise systems.
