# FinThrive — Lead AI Architect

- Generated: 2026-09-12 08:44:46 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4465124558/
- Provider: LinkedIn
- Posted: approximately 2026-09-11 03:44 PM EDT (from '17 hours ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp
- Applicants: 26 applicants
- Work model/location: Remote — United States
- Compensation: Not disclosed for a non-Director/VP/Chief title
- Travel: Not disclosed
- Positioning track: Technical IC
- Fit outcome: FAIL — 84%

## Direct-match strengths

Enterprise AI architecture, GenAI, agents, RAG, document processing, LangChain, AWS Bedrock, vector databases, prompts, MLOps, evaluation, observability, responsible AI, governance, regulated healthcare, patents, and technical mentoring.

## Hard or material gaps

Hard required-skill gap: the posting explicitly requires proven hands-on SFT, LoRA, PEFT, and domain-specific LLM adaptation, which Keith's sources do not establish. Compensation is also undisclosed for a non-Director/VP/Chief title. Azure AI/OpenAI and Databricks are listed among alternatives, so AWS Bedrock provides cloud-platform coverage but does not cure the fine-tuning requirement.

## Evidence map

1. 15+ years software engineering or architecture (weight 3, evidence 3/3) — Twenty-nine years of software architecture and production delivery.
2. 8+ years enterprise AI-driven solutions (weight 3, evidence 3/3) — Long enterprise AI/ML, data, knowledge-discovery, and production-platform record.
3. Agentic AI, GenAI, RAG, and document intelligence (weight 3, evidence 3/3) — Direct agents, LLMs, RAG, semantic retrieval, and document-processing evidence.
4. SFT, LoRA, PEFT, and domain adaptation (weight 3, evidence 0/3) — Required hands-on fine-tuning techniques are unsupported.
5. LangChain, vectors, and cloud AI (weight 2, evidence 3/3) — Direct LangChain/LangGraph, PGVector, AWS Bedrock, and SageMaker evidence.
6. MLOps, observability, governance, and Responsible AI (weight 3, evidence 3/3) — Direct production evaluation, monitoring, guardrails, drift, security, and governance.
7. Regulated healthcare environment (weight 2, evidence 3/3) — Direct healthcare, HIPAA, FDA-cleared, and regulated-enterprise experience.
8. Compensation (weight 3, evidence 0/3) — Undisclosed for a non-Director/VP/Chief title.

## Keyword diagnostic

Excellent architecture, agentic AI, RAG, governance, and healthcare overlap; disqualified by mandatory fine-tuning depth and undisclosed compensation.

## Full normalized job description

Location:
Remote, USA
Employment Type:
Full-Time | Exempt
About the Role
FinThrive is building the future of healthcare revenue cycle management through advanced AI capabilities. As
Lead AI Architect
, you will define and evolve the enterprise architecture for FinThrive's AI ecosystem—enabling Large Language Models (LLMs), Agentic AI, and advanced automation to transform how we deliver value.
This is a strategic, high-impact role. You’ll partner with business, product, architecture, and engineering leaders to set a scalable AI vision, shape technology decisions, and guide the organization in responsible, secure, and innovative AI adoption.
What You Will Do
Define and maintain AI architecture standards, reference models, and technology roadmaps.
Architect and integrate
Agentic AI systems
,
Generative AI
,
Document Intelligence
, and
retrieval-augmented generation (RAG)
into FinThrive products and platforms.
Lead
fine-tuning and customization of AI models
using advanced techniques:
Supervised Fine-Tuning (SFT)
Parameter-Efficient Fine-Tuning (PEFT)
Low-Rank Adaptation (LoRA)
Continued Pretraining
for domain-specific adaptation
Establish best practices for
prompt engineering
, model evaluation, observability, and AI governance.
Provide architectural leadership for MLOps, Responsible AI, and compliance within a regulated healthcare environment.
Mentor technical leaders in AI design patterns, orchestration frameworks (e.g., LangChain, Semantic Kernel), and vector database solutions.
Collaborate on build vs. buy decisions, cloud platform optimization, and scalable deployments using
Azure AI
,
Azure OpenAI
,
AWS Bedrock
, or equivalent platforms.
What You Bring
15+ years in software engineering, enterprise architecture, or AI platform leadership roles.
8+ years designing AI-driven solutions for enterprise-scale applications.
Proven hands-on expertise in
model fine-tuning (SFT, LoRA, PEFT)
and
domain-specific LLM adaptation
.
Strong command of:
Generative AI
,
Agentic AI
,
RAG
,
Document Intelligence
AI/ML frameworks and orchestration tools (LangChain, Semantic Kernel)
Cloud AI platforms:
Azure AI/OpenAI
,
AWS Bedrock
, Databricks
Knowledge of
MLOps
, AI observability, and governance practices.
Excellent stakeholder engagement and communication skills for influencing enterprise technology strategy.
Preferred Qualifications
Master’s degree in Computer Science, AI, Data Science, or related field.
Experience in regulated industries (Healthcare, Financial Services, Insurance).
Contributions to open-source AI projects, patents, publications, or thought leadership in the AI space.
Skills
Enterprise Architecture | AI Architecture | Generative AI | Agentic AI | Retrieval-Augmented Generation (RAG) | Document Intelligence | Model Fine-Tuning (SFT, LoRA, PEFT) | Azure AI | AWS Bedrock | Vector Databases | Prompt Engineering | MLOps | Responsible AI | AI Governance

## Artifact metadata

- Resume: Not generated because the fit gate returned FAIL.
- Cover letter: Not generated because the fit gate returned FAIL.
- LinkedIn note: Not generated for a FAIL role.
- Google Drive used: No