AI Architect

Streamline Healthcare Solutions

2d • $150,000 - $200,000 • Remote

About The Position

About Streamline Healthcare Solutions Here at Streamline, we strive on building lasting and trusting relationships with our clients, and our employees set the bar. Streamline’s mission is to build innovative technology solutions that empower people who improve behavioral health and quality of life of those in need. We are a high growth technology company that delivers web-based software for healthcare organizations to provide and coordinate all service delivery processes. Streamline has been offering software in the behavioral health marketplace since 2003. Streamline has built and maintains systems for some of the nation’s premier behavioral health organizations using the latest web-based technology. Streamline offers competitive compensation and benefits packages as well as a challenging, yet flexible, work environment that is conducive to collaboration and productivity. A career with Streamline Healthcare Solutions provides opportunities for growth and continued learning in a workplace where individual contribution is valued and recognized. Join us, and advance your career today with a company that is on the cutting edge of the behavioral healthcare technology industry. Summary of the AI Architect The 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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Enterprise 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level