{"id":2360727,"url":"https://alion.io/job/finthrive-33365-lead-ai-architect","title":"33365-Lead AI Architect","company":{"id":2009803,"name":"FinThrive","domain":"finthrive.com","url":"https://alion.io/company/finthrive","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Dayforce","truth_index":{"grade":"A","score":89,"open_postings":9,"ghost_share":0,"stale_share":0.444,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":165000,"max_usd":289000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":166},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"PEFT","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SFT","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-09-11T04:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-20T03:38:00Z","board_verified":true,"closed_at":null,"days_open":38,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":38},"description":"About the Role\nImpact you will make \nJoin a group of highly talented and motivated data scientists, data engineers, and AI engineers with significant healthcare experience. Define and evolve the enterprise architecture for FinThrive's AI ecosystem, ensuring AI capabilities are effectively integrated across products, platforms, data assets, workflows, and business processes. Partner with business, product, engineering, security, and technology leaders to establish a scalable and sustainable AI strategy that accelerates innovation while ensuring security, compliance, reliability, and operational excellence across the organization. Build the architectural foundation that enables FinThrive to leverage Agentic AI, intelligent automation, machine learning, and advanced analytics to transform healthcare revenue cycle management workflows.\nWhat you will do\nDefine and maintain the architectural vision, principles, standards, and reference architectures for FinThrive's AI platform and AI-enabled products.\nLead the long-term evolution of AI capabilities, including agentic AI, retrieval-augmented generation (RAG), knowledge systems, intelligent automation, machine learning, and emerging AI technologies.\nDefine how AI capabilities, intelligent agents, automation services, knowledge systems, and machine learning solutions integrate with existing and future FinThrive products and platforms.\nEstablish enterprise integration patterns, AI architecture standards, governance frameworks, and operational processes that ensure consistency across AI and non-AI systems.\nGuide strategic technology decisions involving AI platforms, cloud providers, model hosting strategies, vector databases, orchestration frameworks, AI infrastructure, build-versus-buy evaluations, and platform investments.\nCollaborate with product, engineering, architecture, security, compliance, and executive leadership teams to align AI investments with business strategy, application portfolio roadmaps, and enterprise architecture objectives.\nLead architecture reviews for major AI initiatives and provide guidance on system design, scalability, resiliency, interoperability, security, compliance, and cost optimization.\nDevelop multi-year technology roadmaps that identify opportunities for AI enablement across FinThrive's product portfolio and business operations.\nCreate reusable architecture patterns and technical guidance that enable engineering teams to deliver consistent, scalable, secure, and maintainable AI solutions.\nResearch emerging technologies and industry trends, evaluating their applicability to FinThrive's healthcare revenue cycle management and AI strategies.\nMentor Lead AI Engineers, Senior II AI Engineers, and other technical leaders while fostering a culture of architectural excellence, collaboration, innovation, and continuous learning.\nProvide hands-on technical leadership through prototypes, proof-of-concepts, design reviews, and critical problem resolution when necessary.\nWhat you will bring\nBachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Engineering, Software Engineering, or a related technical discipline.\n15+ years of experience in software engineering, platform engineering, machine learning, data engineering, solution architecture, enterprise architecture, or related technical leadership roles.\n8+ years of experience designing enterprise AI, machine learning, analytics, or intelligent automation solutions.\nDeep understanding of generative AI, agentic AI, retrieval-augmented generation (RAG), natural language processing, machine learning, information retrieval, intelligent automation platforms, and techniques for model adaptation including prompt engineering, fine-tuning, parameter-efficient fine-tuning (PEFT), and retrieval-based approaches.\nExperience evaluating and selecting model customization strategies, including prompting, RAG, fine-tuning, continued pretraining, and domain-specific model adaptation.\nExperience designing enterprise-scale architectures across cloud, application, integration, data, security, and AI domains.\nExperience architecting AI solutions utilizing platforms such as Azure AI, Azure OpenAI, Azure AI Search, Databricks, AWS Bedrock, SageMaker, or equivalent technologies.\nStrong understanding of modern AI frameworks, orchestration platforms, open-weight models, evaluation frameworks, observability tooling, and AI governance practices.\nExperience establishing architecture standards, technology roadmaps, governance processes, and enterprise engineering practices.\nDemonstrated experience designing architectures that span multiple applications, platforms, business domains, and technology stacks.\nProven ability to influence technical direction across multiple teams, products, and organizational boundaries.\nExcellent communication, presentation, and stakeholder-management skills with the ability to communicate architecture strategy and technical tradeoffs to executive leadership.\nStrong understanding of software development lifecycle practices, DevSecOps, MLOps, platform engineering, security principles, and cloud-native architectures.\nWhat we would like to see\nMaster's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Enterprise Architecture, or a related technical discipline.\nExperience serving as an Enterprise Architect, AI Architect, Principal Architect, Solution Architect, or similar strategic architecture role.\nExperience building and governing AI solutions in regulated industries such as Healthcare, Financial Services, Insurance, or Consumer Credit.\nExperience developing AI solutions utilizing healthcare standards, claims data, clinical data, FHIR, HL7, medical coding systems, knowledge graphs, or other healthcare-specific technologies.\nExperience defining responsible AI frameworks, AI governance programs, model risk management practices, and enterprise AI policies.\nExperience evaluating and deploying open-weight foundation models and enterprise AI platforms in both cloud-hosted and self-hosted environments.\nExperience fine-tuning, evaluating, deploying, or governing open-weight foundation models using techniques such as supervised fine-tuning (SFT), parameter-efficient fine-tuning (LoRA/PEFT), reinforcement learning methods, or synthetic data generation.\nExperience developing enterprise technology roadmaps and guiding platform modernization initiatives.\nExperience leading enterprise-scale multi-agent platforms, intelligent automation programs, or large-scale AI transformation initiatives.\nContributions to open-source projects, patents, publications, conference presentations, industry forums, or other thought leadership activities.","description_format":"text","description_chars":6741,"description_truncated":false,"requirements":{"experience_years_min":15,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Revenue Cycle & Medical Billing"],"lifecycle":[{"event":"open","at":"2026-10-12T15:49:13Z"}],"visa":[],"liveness":{"score":61,"band":"ok","label":"Likely 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