Job Requirements
Position Overview
As the Principal AI Architect for Healthcare Contact Center Solutions, you will serve as the strategic visionary and technical authority responsible for modernizing our member and provider experience platform. In this high-visibility role, you will design, architect, and deliver enterprise-grade AI capabilities across conversational interfaces, real-time agent support systems, and predictive analytics engines.
You will bridge the gap between technical execution and healthcare operations-working directly with Cloud Engineers, Machine Learning Engineers, MLOps specialists, and CRM Developers (Salesforce Health Cloud / Microsoft Dynamics) to embed secure, HIPAA-compliant AI models into daily workflows.
Key Responsibilities
Strategic Leadership & Solution Design
- Lead the end-to-end strategy, architectural blueprinting, and implementation of AI capabilities across all Contact Center interaction channels (Voice, Web Chat, SMS).
- Identify high-value AI opportunities within member services, claims inquiry, benefit verification, and provider relations to draft actionable technical roadmaps.
- Act as the technical SME on cloud-native conversational AI suites (Google GCP CCAI / Vertex AI or Azure AI / Copilot Studio).
Technical Architecture & Systems Integration
- Architect production-grade Generative AI, Retrieval-Augmented Generation (RAG), and Natural Language Understanding (NLU) architectures for real-time agent assist and automated self-service voicebots/chatbots.
- Partner with CRM development teams to seamlessly integrate AI insights, automated call summaries, and next-best-action recommendations directly into agent desktops.
- Establish MLOps standards, continuous integration pipelines, continuous evaluation loops, and system observability for production AI models.
Data Privacy, Security, and Compliance
- Architect robust Protected Health Information (PHI) and Personally Identifiable Information (PII) redaction pipelines across voice streams and text transcripts.
- Enforce strict compliance with HIPAA, CMS guidelines, and state regulations across all data ingestion, training, and inference workflows.
- Design explainable AI models with clear source attribution to ensure auditability and human-in-the-loop oversight.
Team Enablement & Collaboration
- Drive technical cross-functional alignment between Cloud Infrastructure, Data Engineering, Security, and Business Operations teams.
- Conduct technical training, research emerging AI trends, and mentor engineering teams on AI/ML best practices and architectural patterns.
Required Qualifications
Experience & Education
- Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or Data Science (or equivalent practical experience).
- 5+ years of experience as an AI Architect, Enterprise Architect, or Principal ML Engineer designing and deploying distributed production systems.
- Proven track record architecting enterprise solutions on Google Cloud Platform (GCP) or Microsoft Azure.
Technical Core Competencies
- AI/ML Architectures: Deep expertise in LLMs, RAG, Conversational AI, Speech-to-Text (STT), Text-to-Speech (TTS), and Natural Language Processing (NLP).
- Cloud Native Platforms: Hands-on architecture experience with GCP (Dialogflow CX, Vertex AI, BigQuery) OR Azure (Azure OpenAI Service, Copilot Studio, Azure Machine Learning).
- Software Engineering: Strong proficiency in system design, API design (REST/gRPC), microservices architecture, and enterprise integration patterns.
- Data Security: Solid understanding of data protection mechanisms, tokenization, anonymization, and encryption strategies.
Work Experience
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