AI Architect, Principal Frontline AI Engineer - Healthcare

Role Brief:

We are seeking an AI Architect – Healthcare AI Transformation to partner with one of the largest healthcare payers in the United States to design and scale AI-driven transformation initiatives. This role operates at the intersection of AI architecture, healthcare operations, enterprise technology, and business transformation.
The AI Architect will work directly with executive leaders, business stakeholders, clinical and operational teams, and engineering organizations to identify high-value AI opportunities, define enterprise AI strategies, architect solutions, and guide implementation from concept through production.
This role goes beyond traditional architecture. The successful candidate will combine deep AI engineering expertise with healthcare domain understanding to redesign business processes using Generative AI, Agentic AI, LLMs, and intelligent automation while enabling organizations to become AI-native.

Key Responsibilities:

• Partner directly with healthcare executives, business stakeholders, clinical leaders, and technology teams to identify AI transformation opportunities and define AI-driven solutions.
• Translate complex healthcare business challenges into scalable AI architectures, technical strategies, and implementation roadmaps.
• Design and architect enterprise AI solutions leveraging Generative AI, Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and intelligent automation.
• Define AI solution patterns including multi-agent architectures, workflow orchestration, knowledge retrieval systems, and enterprise AI integrations.
• Lead AI solution development from discovery and architecture through prototyping, production deployment, and optimization.
• Design AI-enabled workflows to transform healthcare operations including claims processing, prior authorization, care management, provider operations, member services, and payment integrity.
• Build and guide implementation of AI applications using modern AI frameworks, cloud platforms, APIs, and enterprise data ecosystems.
• Collaborate with engineering, data science, product, security, and governance teams to ensure scalable, secure, and responsible AI adoption.
• Establish AI architecture standards, best practices, reusable frameworks, and accelerators for enterprise AI delivery.
• Support AI governance practices including model monitoring, explainability, security, compliance, and responsible AI implementation.
• Lead technical workshops, architecture reviews, executive presentations, and solution demonstrations with client stakeholders.
• Mentor engineering teams and enable business teams to adopt AI tools, workflows, and AI-native operating models.

Required Skills & Experience:

• 10+ years of experience in software engineering, AI engineering, machine learning, enterprise architecture, or digital transformation.
• Hands-on experience designing and implementing Generative AI and AI/ML solutions in enterprise environments.
• Strong understanding of Large Language Models (LLMs), AI agents, prompt engineering, RAG architectures, and AI application patterns.
• Experience architecting and delivering production-grade AI solutions from concept through deployment.
• Strong software engineering background with proficiency in Python, APIs, microservices, and cloud-based application development.
• Experience designing AI workflows, orchestration patterns, tool integrations, and enterprise AI architectures.
• Experience working with cloud AI platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Ability to translate business requirements into technical architectures and communicate solutions to both technical and executive audiences.
• Experience working directly with business stakeholders, clients, or cross-functional teams in a consulting or enterprise environment.
• Experience with AI governance, security, monitoring, evaluation frameworks, and responsible AI practices.
• Healthcare industry experience with understanding of payer/provider workflows, healthcare operations, and regulated environments.
• Knowledge of healthcare compliance considerations including HIPAA and healthcare data privacy.

Good to Have:

• Experience as an AI Architect, Forward Deployed Engineer, Solutions Architect, or Consulting Architect.
• Experience building agentic AI systems using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or Semantic Kernel.
• Experience with Claude (Anthropic), OpenAI, Gemini, or other enterprise LLM platforms.
• Experience developing healthcare AI solutions for:
     o Claims processing and adjudication
     o Prior authorization
     o Utilization management 
     o Care management
     o Member/provider engagement
     o Revenue cycle management
     o Payment integrity

• Familiarity with healthcare data standards including HL7, FHIR, ICD-10, CPT, and claims data structures.
• Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and enterprise search solutions.
• Experience integrating AI solutions with enterprise platforms such as Salesforce, ServiceNow, Epic, or healthcare workflow systems.
• Experience creating reusable AI accelerators, reference architectures, and enterprise AI frameworks.
• Experience supporting AI adoption, enablement, and training for business and engineering teams.
• Experience working in highly regulated industries where security, governance, and auditability are required.