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Lead Engineer - II_AI
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CitiusTech Inc
Rochester, MN (In Person)
Full-Time
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Job Description
Lead Engineer - II_AI CitiusTech Inc - 3.7 Rochester, MN Job Details 22 hours ago Qualifications AI models Data model design Azure SQL Database Cloud identity and access management (IAM) Commercial use (data warehousing systems) Data visualization software proficiency Data Integration (Data management) Cloud Logging Azure Function proficiency Cloud data warehouses Azure IaaS Achieving HIPAA compliance Technical documentation Infrastructure as Code (IaC) DevOps Spark
HIPAA AI
platforms (beyond public GPTs) Object storage systems Machine learning projects Security compliance frameworks implementation Data governance Prompt engineering SQL Azure Synapse Analytics RBAC Machine learning cloud services Business intelligence tools Spark implementationAzure Key Vault Full Job Description Job ID:
877978 7 - 10 Years 1 Opening Rochester MN Role description Role Summary Senior engineer to build and operate Azure-based data and AI solutions for healthcare. Primary depth is general Azure (compute, storage, networking, data services, security) and Azure AI Foundry for model and agent workloads. Works across Microsoft Fabric and other Azure data platforms as needed. Core Responsibilities- Build and operate Azure cloud workloads — compute, storage, networking, identity, and managed data services.
- Develop and deploy AI solutions on Azure AI Foundry — models, agents, prompt flows, evaluations, and managed endpoints.
- Implement RAG and agent patterns using Azure AI Search, model catalog, and Foundry tools.
- Build data pipelines across relevant Azure data platforms (Microsoft Fabric, Azure Data Factory, Synapse, ADLS).
- Implement
HIPAA/HITRUST
controls — encryption, audit logging, BAA-covered services, governance guardrails.- Ship via Git and CI/CD (Azure DevOps or GitHub Actions); document patterns for the rest of the team.
Technical Requirements:
Azure Cloud (Primary)- 7+ years of cloud engineering experience, with significant time on Azure.
- Hands-on across core Azure services — compute (App Service, AKS, Functions), storage (ADLS Gen2, Blob), networking (VNets, NSGs, Private Link), and Entra
ID / RBAC.
- Azure managed data services — Azure SQL, Cosmos DB, Synapse, Azure Data Factory.
- Infrastructure as Code with Terraform or Bicep; CI/CD via Azure DevOps or GitHub Actions.
- Security fundamentals — Key Vault, managed identities, private endpoints, encryption at rest and in transit. Azure AI Foundry (Primary)
- Hands-on with Azure AI Foundry — model deployment, prompt flow, evaluation, and managed endpoints.
- Building agents and tool-using workflows in Foundry.
- RAG implementations using Azure AI Search and embedding models.
- Working with the Foundry model catalog (open-source and proprietary models).
- Observability and guardrails for AI workloads — content safety, telemetry, and quality metrics. Microsoft Fabric & Other Data Platforms
- Working knowledge of Microsoft Fabric — OneLake, Lakehouse, Fabric SQL Warehouse, Data Factory pipelines, Spark Notebooks, Power BI.
- Medallion architecture (Bronze/Silver/Gold) and Delta Lake.
- Data modeling fundamentals — dimensional modeling, lakehouse patterns.
- Comfortable picking up new Azure data services as the platform evolves. Governance & Compliance
- Hands-on implementing
HIPAA/HITRUST
controls in Azure — encryption, audit logging, BAA-covered services.- Row-/column-/object-level security patterns in Azure data services.
- Documenting changes well enough to navigate governance and approval processes.
Other Requirements:
- Hands-on operator: Builds and ships, not just designs; takes responsibility for what runs in production.
Troubleshooter:
Diagnoses issues across Azure services and Foundry workloads — pipelines, deployments, performance.- Curious about
AI:
Tracks Foundry, Azure AI, and adjacent platform evolution; brings new capabilities back.- Multi-platform awareness: Operates fluently across Azure data and AI services; understands tradeoffs between them.
- Clear documentation: Documents patterns and decisions so others on the team can follow them.