Senior Platform & Infrastructure Engineer

About the Role

The Senior Platform & Infrastructure Engineer is the principal technical contributor within the NXHS Corporate IT Platform & Operations team. This dual-mission role focuses on designing, building, and operationalizing AI and agentic automation solutions that transform clinical and business operations across all Nexus Health Systems facilities, while also ensuring the enterprise infrastructure supporting these systems is reliable, secure, and HIPAA-compliant.

NXHS currently operates an NVIDIA stack for on-premises agentic AI but maintains platform flexibility, potentially incorporating Azure AI Foundry, AWS agentic services, or other emerging platforms. The ideal candidate is fluent across cloud and on-premises AI platforms and can adapt as strategic direction evolves.

This role works directly with the Senior Manager, Platform & Operations on R&D initiatives, including multi-agent AI architectures, LLM orchestration, RPA with agentic bolt-ons, and enterprise integration development. It also collaborates closely with the Senior Data Engineer on data layer architecture to ensure AI agents can safely and efficiently query and act on data within the SQL Data Warehouse.

Responsibilities

AI Platform Engineering & Agentic Automation (Primary)

• Design, build, and operationalize multi-agent AI systems on the current NVIDIA stack, while maintaining the ability to architect equivalent solutions on Azure AI Foundry, AWS agentic services, or other platforms as the organization’s strategic direction evolves.
• Develop agent orchestration, swarm architectures, task decomposition, and inter-agent communication patterns for clinical and operational use cases.
• Architect and implement memory permanence and learning-over-time capabilities for AI agents, including vector store design, RAG (Retrieval-Augmented Generation) pipelines, embedding strategies, and state management across agent sessions.
• Build integration layers between AI services and enterprise platforms, including Microsoft 365 (Graph API, core services), SQL Data Warehouse, and clinical systems, enabling agents to consume and act on organizational data.
• Develop and deploy LLM-powered solutions using orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent), including prompt engineering at a systems level, tool/function calling architectures, and chain-of-thought workflows.
• Design and implement RPA (Robotic Process Automation) workflows with agentic AI bolt-ons, automating clinical and administrative processes that currently require manual intervention.
• Spin up, configure, and manage AI model deployments across multiple platforms — on-premises GPU infrastructure (NVIDIA), Azure AI Foundry, and AWS agentic/AI services, including model selection, fine-tuning, and performance optimization.
• Build REST APIs, webhooks, middleware, and connector services that bridge AI/agent outputs to front-end applications, enabling end-user interaction with intelligent systems.
• Partner closely with the Senior Data Engineer on all data layer work, including enabling AI agent access to the SQL Data Warehouse, designing query patterns for autonomous retrieval, building ETL-to-agent handoff points, and co-developing data schemas that support both BI reporting and agentic consumption.
• Conduct hands-on R&D on emerging AI platforms, tools, and architectures with limited vendor documentation or community support.

Enterprise Infrastructure Engineering (Secondary)

• Design, engineer, and operate enterprise infrastructure platforms across on-premises and hybrid environments, including compute, virtualization (VMware vSphere / Hyper-V), storage, and backup/DR solutions that protect patient data and clinical systems.
• Architect and manage Microsoft Azure hybrid cloud environments, including compute, networking, identity (Entra ID), and security services aligned with NXHS compliance requirements.
• Develop Infrastructure-as-Code (IaC) using Terraform for automated, auditable provisioning across clinical and administrative environments.
• Architect, manage, and troubleshoot enterprise networking (LAN/WAN, VLANs, routing/switching, wireless, VPN, firewall) across corporate and clinical facilities.
• Administer Microsoft 365 tenant services (Exchange Online, SharePoint, Teams), including security configuration, DLP, and retention policies aligned with HIPAA requirements.
• Ensure infrastructure configurations comply with HIPAA, CIS benchmarks, and organizational security baselines. Partner with cybersecurity and IT leadership on identity governance, vulnerability remediation, and infrastructure hardening.
• Deploy and manage the Microsoft Defender security stack (Endpoint, Servers, Cloud, Identity) across hybrid infrastructure.

Project Leadership & Collaboration

• Serve as the primary R&D partner to the Senior Manager, Platform & Operations on AI and agentic initiatives, picking up technical threads independently when leadership bandwidth is constrained.
• Partner with Clinical Informatics, Data Engineering, and Service Delivery teams to ensure platform readiness for AI-powered application deployments, clinical system implementations, and enterprise modernization.
• Evaluate emerging AI platforms, agent frameworks, and infrastructure capabilities; deliver strategic recommendations to IT leadership on architecture decisions.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, or a related field required; equivalent professional experience considered.
• 10+ years of hands-on experience in infrastructure engineering or platform development, with demonstrated ability to operate at a senior level across enterprise environments.
• 2+ years of hands-on AI/ML engineering experience, building with LLMs, agent frameworks, RAG pipelines, or agentic automation in a real environment (not just coursework or tutorials).
• Demonstrated experience building and deploying AI/ML solutions beyond proof-of-concept, whether in production, internal tooling, or serious R&D.
• Healthcare IT experience preferred, particularly supporting clinical environments with 24/7 uptime requirements.
• Experience with multi-agent system design patterns: shared vs. isolated memory, message bus architectures, agent specialization, and tool-use frameworks.
• Experience supporting healthcare EHR platforms (Meditech, Epic, or similar) from an infrastructure perspective.
• SQL proficiency sufficient to partner daily with the Senior Data Engineer on warehouse schema design, query optimization, data pipeline architecture, and AI agent data access patterns.
• Comfort operating with minimal vendor support on bleeding-edge platforms. Proven ability to pioneer through ambiguity via documentation, experimentation, and community engagement.

Qualifications

Certifications

• Azure Administrator, Azure AI Engineer Associate, Azure Solutions Architect, AWS Certified Solutions Architect, AWS Certified Machine Learning Engineer, NVIDIA Certified Professional, or equivalent.

AI & Agentic Engineering Skills

• LLM orchestration frameworks: LangChain, LlamaIndex, Semantic Kernel, or equivalent agent-building toolkits.
• Vector databases and embedding pipelines (Pinecone, Qdrant, pgvector, or equivalent) for RAG and agent memory architectures.
• NVIDIA AI stack: Nemotron models, NVIDIA Guardrails, DGX administration, GPU compute management.
• Cloud AI services across multiple providers: Azure AI Foundry (OpenAI, Cognitive Services), AWS AI/agentic services (Bedrock, SageMaker), or equivalent.
• Python development for AI/ML workflows, API development (FastAPI, Flask), and scripting/automation.
• REST API design, webhook architectures, OAuth/app registration, and Microsoft Graph API integration for programmatic access to M365 services.
• RPA platforms and intelligent automation design, with an understanding of how agentic AI extends traditional RPA capabilities.

Infrastructure & Platform Skills

• Microsoft Azure ecosystem: hybrid cloud architecture, identity (Entra ID), networking, and security.
• Enterprise virtualization (VMware or Hyper-V), Windows Server and Linux administration, and OS hardening.
• Enterprise networking: TCP/IP, VLANs, routing/switching, firewall management, VPN technologies.
• Infrastructure-as-Code (Terraform preferred) and PowerShell scripting for automation and configuration management.
• Microsoft 365 enterprise administration, Microsoft Defender security stack, and HIPAA Security Rule requirements for infrastructure.

Technical Competencies

The following tools, platforms, and systems are directly relevant to this role within the NXHS environment:

Domain Technologies & Platforms AI & Agentic NVIDIA stack (Nemtron, Guardrails, etc.), LangChain, LlamaIndex, Semantic Kernel, AutoGen, vector databases (Pinecone, Qdrant, pgvector), RAG pipelines, embedding models Cloud AI Services Azure AI Foundry, AWS Bedrock, AWS SageMaker, model hosting & inference (multi-cloud) Development Python (FastAPI, Flask), REST APIs, Webhooks, Microsoft Graph API RPA & Automation Power Automate, intelligent automation platforms, agentic RPA design patterns Cloud & Hybrid Microsoft Azure (IaaS, PaaS), Azure DevOps, Azure AI Foundry, AWS (Bedrock, SageMaker) Microsoft 365 Exchange Online, SharePoint, OneDrive, Teams, Graph API, DLP Virtualization VMware vSphere / vCenter, Microsoft Hyper-V Identity & Access Microsoft Entra ID, Active Directory, Group Policy, PKI, Conditional Access Server Platforms Windows Server, Enterprise Linux Distros Storage & Backup Enterprise SAN, Veeam, Druva Networking TCP/IP, DNS, DHCP, VLANs, VPN, Aruba switches & APs, Cisco firewalls Automation & IaC Terraform, Python, PowerShell Healthcare Meditech EMR, Fukuda, BD Pyxis, 3M Security Microsoft Defender (full stack), CIS Benchmarks, HIPAA controls