Staff AI Engineer

🕒 April 21

🌵 Arizona, California, +4 more states – Remote

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💵 $147.9k - $254.8k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

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👻 Ghost score 35%

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Logo of SCAN

SCAN

1001 - 5000 employees

Founded 1977

🏥 Healthcare

⚕️ Healthcare Insurance

👥 B2C

Healthcare • Healthcare Insurance • B2C

SCAN is a mission-driven healthcare organization focused on reinventing aging by delivering evidence-based, patient-centered care and coverage for older adults. It operates an integrated portfolio including health insurance plans with innovative benefits, in-home and virtual primary care, support programs for caregivers and homebound older adults, and specialized services for vulnerable populations. SCAN also invests in and partners with companies that advance care models and resources to help older adults remain healthy and independent at home.

📋 Description

• Define the end-to-end reference architecture for AI and data/storage systems across Azure AI Foundry, Azure AI Services, Azure AI Search, Azure Databricks/Fabric, and Snowflake • Design integration blueprints for RAG workflows, data pipelines, agentic frameworks, and our enterprise GPT solution • Establish standards for model deployment, versioning, prompt management, and telemetry within Azure AI Foundry • Build and maintain scalable cloud environments for model training, evaluation, and inference • Oversee vector database design (Azure AI Search or equivalent) and integration with Snowflake/Fabric data hubs • Implement high-availability, cost-optimized compute and storage strategies for AI workloads • Partner with IT Security to ensure alignment with HIPAA, Responsible AI, and internal compliance requirements • Design pipelines and event-driven architectures using Azure Functions, Logic Apps, and API Management • Automate ingestion and evaluation processes for Document Intelligence, AI Search, and other Azure AI Services • Integrate monitoring, audit, and feedback loops to ensure operational transparency and continuous improvement • Lead architecture reviews and guide solution teams to adhere to Responsible AI and data-management standards • Define metadata, lineage, and model registry conventions for consistent tracking and reuse • Collaborate with engineering, analytics, and business teams to align technical designs with strategic outcomes • Evaluate emerging Azure and open-source technologies to extend SCAN’s AI capabilities

🎯 Requirements

• Deep Expertise in Azure Ecosystem • Proficiency in Azure AI Foundry, Azure AI Services (Language, Vision, Speech, Content Understanding), Azure AI Search, Azure ML, Databricks, and Fabric • Familiarity with model registries, MLOps, and deployment frameworks (CI/CD, containers, APIs) • Proven ability to design scalable, secure, and modular cloud architectures for AI and data workloads • Strong understanding of network design, IAM, data governance, and enterprise integration patterns • Knowledge of LLM architectures, retrieval-augmented generation, embedding pipelines, and evaluation frameworks • Experience enabling RAG and multi-agent applications through Azure AI Foundry and related SDKs • Understanding of data modeling, knowledge graphs, and semantic search design • Ability to define data contracts, metadata taxonomies, and lineage tracking for AI solutions • Demonstrated commitment to secure, auditable, and explainable AI design • Familiarity with healthcare data standards (HIPAA, CMS, PHI/PII protection) • Adept at influencing cross-functional stakeholders and translating architecture into actionable guidance • Comfortable working in a fast-evolving environment balancing experimentation with operational rigor • Strong written and verbal communication skills for technical and executive audiences

🏖️ Benefits

• Annual employee bonus program • Robust Wellness Program • Generous paid-time-off (PTO) • 11 paid holidays per year • 1 floating holiday • Birthday off • 2 volunteer days • Excellent 401(k) Retirement Saving Plan with employer match • Robust employee recognition program • Tuition reimbursement

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