AI and Cloud Architect
Job Description:
- Design the foundation that makes intelligent systems scale for our enterprise
- Define and govern the architecture that powers SCAN’s AI and automation capabilities
- Bridge infrastructure and innovation, ensuring every AI and cloud solution is built on secure, performant, and reusable patterns
- Bring a holistic view to enable experimentation while maintaining enterprise standards for reliability, governance, and compliance
- 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 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
- 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
- Serve as a key contributor to the AI Architecture Review Board and cloud optimization initiatives
- Evaluate emerging Azure and open-source technologies to extend SCAN’s AI capabilities
- Prototype new integration patterns for multi-agent collaboration, knowledge management, and semantic data discovery
- Coach engineers on architectural best practices and help shape the long-term technical roadmap
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:
- An annual employee bonus program
- Robust Wellness Program
- Generous paid-time-off (PTO)
- 11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
- Excellent 401(k) Retirement Saving Plan with employer match
- Robust employee recognition program
- Tuition reimbursement
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