AI Architect

Responsibilities

The following outlines the essential functions necessary for this role. It is intended as a guide and not an exhaustive list of all duties or responsibilities that may be assigned.

AI Strategy & Architecture

• Spearhead the design and implementation of transformative AI initiatives leveraging large language models (LLMs), Generative AI, and Machine Learning to enhance and modernize core business operations.

• Architect and deploy secure, scalable, cloud-native infrastructure and automation pipelines across clinical and administrative domains (e.g., Azure, Google Cloud).

• Design and implement Agentic Workflows and multi-agent orchestration systems to automate critical business processes.

Conversational AI & Integration

• Develop and deploy Voice AI agents and LLM/RAG conversational systems to streamline employee interactions and internal/external communications (e.g., OpenAI, Gemini, Vapi, Twilio).

• Integrate AI capabilities into enterprise communication platforms (e.g., Google Workspace) to enable natural-language interfaces for non-technical teams.

Data Integrity & Compliance

• Establish robust data analysis and quality-assurance agents to ensure the integrity of clinical and operational data (e.g., LLM-as-a-Judge, IAA).

• Develop and manage comprehensive AI benchmarking, monitoring, and testing frameworks to ensure performance, reliability, and compliance (including HIPAA).

Technology Leadership

• Collaborate with clinical, compliance, and administrative leaders to ensure AI solutions drive measurable outcomes such as reduced intake time, improved operational efficiency, and increased utilization of clinical staff.

Ethics, Compliance & Reporting

• Adhere to all organizational policies, procedures, and applicable federal and state regulations.

• Maintain responsibility for promptly reporting any violations of company policies or ethical guidelines.

Required Qualifications, Skills, and Knowledge

• Bachelor’s degree in Information Technology, Computer Science, or related discipline.

• Proven ability to design technology solutions that comply with strict regulatory standards, especially HIPAA, in healthcare technology environments.

• Experience with workflow automation platforms (e.g., Workato, Make, n8n) and integration across operational toolsets such as Google Workspace.

• Working knowledge of laptops/desktops and common IT troubleshooting.

• Proficiency with Microsoft Office Suite (Word, Excel) and G Suite (Gmail, Drive, Docs, Sheets, Google Meet).

• Deep technical proficiency in AI/ML model deployment, including LLMs and RAG architectures.

• Extensive experience with cloud infrastructure (Azure, Google Cloud, AWS) and cloud-native service implementations.

• Hands-on experience with AI/ML platforms and APIs including OpenAI API, Gemini, and custom model development.

• Proficiency in Python and C# for enterprise application development, automation, and AI pipelines.

• Demonstrated experience in event-driven architecture, REST APIs, message buses, and database technologies (Cosmos DB, SQL).

• Ability to follow written instructions and work effectively with computer systems and software.

• Strong expressive and receptive communication skills.

• 8 years building production-grade software.

• 5 years working with Machine Learning models.

• 5 years working with cloud infrastructure and cloud-native AI/ML applications.

• 2 years in LLM/Agentic/RAG systems, including multi-agent orchestration frameworks (Semantic Kernel, LangGraph) and tool-calling.

• Deep Azure expertise, including:

• AKS

• Azure API Management

• Event Hubs / Service Bus

• Cosmos DB / Azure SQL / Postgres

• Azure AI Search (vector/hybrid)

• Key Vault

• Monitor / OpenTelemetry