Lead AI Architect

🔥 3 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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FinThrive

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏥 Healthcare

☁️ SaaS

🤖 Artificial Intelligence

💰 $1M Series A on 2010-02

Healthcare • SaaS • Artificial Intelligence

FinThrive is a healthcare revenue cycle management (RCM) technology company that provides AI-powered, data-intelligence solutions to hospitals, health systems, ambulatory and physician practices, payers and life sciences organizations. Its FinThrive Fusion platform unifies siloed revenue-cycle data to enable predictive analytics, agentic AI workflows, and operational intelligence. Product offerings include patient access, revenue integrity (charge capture and compliance), revenue optimization (claims, denials prevention, payment accuracy), enterprise analytics and learning content designed to improve cash flow, reduce denials and streamline revenue operations. FinThrive positions itself as a SaaS provider delivering AI and automation capabilities to improve financial performance and operational efficiency across the healthcare revenue cycle.

📋 Description

• Define and maintain the architectural vision, principles, standards, and reference architectures for FinThrive's AI platform and AI-enabled products • Lead the long-term evolution of agentic AI, RAG, knowledge systems, intelligent automation, machine learning, and emerging AI technologies • Define integration of AI capabilities, intelligent agents, automation services, knowledge systems, and machine learning solutions with FinThrive products and platforms • Establish enterprise integration patterns, AI architecture standards, governance frameworks, and operational processes • Guide strategic technology decisions involving AI platforms, cloud providers, model hosting, vector databases, orchestration frameworks, AI infrastructure, build-versus-buy evaluations, and platform investments • Collaborate with product, engineering, architecture, security, compliance, and executive leadership teams • Lead architecture reviews for major AI initiatives, covering system design, scalability, resiliency, interoperability, security, compliance, and cost optimization • Develop multi-year technology roadmaps for AI enablement across FinThrive's product portfolio and business operations • Create reusable architecture patterns and technical guidance for consistent, scalable, secure, and maintainable AI solutions • Research emerging technologies and industry trends for healthcare revenue cycle management and AI strategies • Mentor Lead AI Engineers, Senior II AI Engineers, and other technical leaders • Provide hands-on technical leadership through prototypes, proof-of-concepts, design reviews, and critical problem resolution

🎯 Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Engineering, Software Engineering, or a related technical discipline • 15+ years of experience in software engineering, platform engineering, machine learning, data engineering, solution architecture, enterprise architecture, or related technical leadership roles • 8+ years of experience designing enterprise AI, machine learning, analytics, or intelligent automation solutions • Deep understanding of generative AI, agentic AI, retrieval-augmented generation (RAG), natural language processing, machine learning, information retrieval, intelligent automation platforms, prompt engineering, fine-tuning, parameter-efficient fine-tuning (PEFT), and retrieval-based approaches • Experience evaluating and selecting model customization strategies, including prompting, RAG, fine-tuning, continued pretraining, and domain-specific model adaptation • Experience designing enterprise-scale architectures across cloud, application, integration, data, security, and AI domains • Experience architecting AI solutions using Azure AI, Azure OpenAI, Azure AI Search, Databricks, AWS Bedrock, SageMaker, or equivalent technologies • Strong understanding of modern AI frameworks, orchestration platforms, open-weight models, evaluation frameworks, observability tooling, and AI governance practices • Experience establishing architecture standards, technology roadmaps, governance processes, and enterprise engineering practices • Demonstrated experience designing architectures spanning multiple applications, platforms, business domains, and technology stacks • Proven ability to influence technical direction across multiple teams, products, and organizational boundaries • Excellent communication, presentation, and stakeholder-management skills • Strong understanding of software development lifecycle practices, DevSecOps, MLOps, platform engineering, security principles, and cloud-native architectures • Preferred: Master's degree in a related technical discipline • Preferred experience as an Enterprise Architect, AI Architect, Principal Architect, Solution Architect, or similar strategic architecture role • Preferred experience in regulated industries such as Healthcare, Financial Services, Insurance, or Consumer Credit • Preferred experience with healthcare standards, claims data, clinical data, FHIR, HL7, medical coding systems, and knowledge graphs • Preferred experience defining responsible AI frameworks, AI governance programs, model risk management practices, and enterprise AI policies • Preferred experience evaluating and deploying open-weight foundation models in cloud-hosted and self-hosted environments • Preferred experience with SFT, LoRA/PEFT, reinforcement learning methods, and synthetic data generation • Preferred experience developing enterprise technology roadmaps and leading platform modernization initiatives • Preferred experience leading enterprise-scale multi-agent platforms, intelligent automation programs, or large-scale AI transformation initiatives • Preferred contributions to open-source projects, patents, publications, conference presentations, industry forums, or other thought leadership activities