Senior AI Solutions Architect (Remote Opportunity)

Nimbus Data Systems is seeking a Senior AI Solutions Architect to lead the design and implementation of enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA), with responsibility for AI architecture across the JLV contract. The initial assignment will support the Joint Longitudinal Viewer (JLV) AI Search and Summarization initiative, delivering a secure, governed AI-assisted search and summarization MVP for development, clinical evaluation, and designated-user testing in an approved lower environment utilizing Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) within a secure AWS cloud environment. Working closely with Government stakeholders, clinical subject matter experts, software engineers, cybersecurity teams, and DevSecOps personnel, this individual will establish the overall AI solution architecture while ensuring scalability, security, interoperability, Responsible AI, and compliance with Federal cybersecurity and AI governance requirements. Responsibilities: Lead the architecture, design, and implementation of enterprise AI solutions utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Design scalable, secure, and maintainable AI architectures supporting enterprise healthcare applications. Define solution architecture, data flows, system interfaces, AI orchestration, and integration patterns. Evaluate AI technologies, services, and frameworks to support current and future project needs. Ensure architecture supports approved future phases without expanding the authorized MVP scope. Design AI solutions leveraging Amazon Bedrock and AWS cloud services. Architect secure AI pipelines supporting approved document access and processing, retrieval, vector search, prompt orchestration, and AI-assisted summarization. Define strategies for model selection, prompt management, retrieval optimization, and AI performance tuning. Define monitoring and evaluation strategies to detect model, prompt, retrieval, and data drift and address degradation in accuracy, safety, or clinical relevance. Optimize AI architectures for scalability, operational cost, reliability, and response time. Collaborate with DevSecOps teams to support deployment automation and operational readiness. Design integration between AI services and existing enterprise healthcare applications. Define secure interfaces utilizing REST APIs and modern integration patterns. Ensure solutions align with healthcare interoperability standards including FHIR, HL7, and CCD. Collaborate with application development teams to integrate AI capabilities into clinician workflows. Promote consistent architecture patterns and engineering best practices across JLV development teams. Design AI solutions that comply with Federal cybersecurity, privacy, and Responsible AI requirements. Incorporate Human-in-the-Loop (HITL), source traceability, approved data boundaries, retention and purge controls, explainability, auditability, and governance principles into solution architecture. Support Authority to Operate (ATO), AI governance, Security Impact Analysis (SIA), and technology approval activities. Ensure secure handling of Protected Health Information (PHI) and Personally Identifiable Information (PII). Collaborate with cybersecurity teams to implement secure AI architectures and operational controls. Serve as the technical leader for AI architecture across the JLV contract. Mentor software engineers and provide architectural guidance throughout the software development lifecycle. Participate in architecture reviews, design sessions, sprint planning, backlog refinement, and technical estimation. Produce architecture documentation, system design artifacts, interface specifications, and implementation guidance. Present technical approaches and architectural recommendations to Government leadership and stakeholders. Requirements: Bachelor's degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, Data Science, or a related technical field, or equivalent experience. 10+ years designing enterprise software solutions. 5+ years designing cloud-native architectures utilizing AWS or comparable cloud platforms. Demonstrated experience architecting Artificial Intelligence, Machine Learning, or Generative AI solutions. Experience implementing enterprise applications utilizing Amazon Bedrock or similar AI platforms. Experience leading technical architecture across multidisciplinary engineering teams. Amazon Bedrock and AWS cloud services Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt engineering, source-grounded AI evaluation, and hallucination testing Vector databases, embeddings, and semantic search REST APIs and enterprise integration Cloud architecture and distributed systems DevSecOps and CI/CD Healthcare interoperability (FHIR, HL7, CCD) Additional Qualifications: Strong understanding of enterprise architecture principles and cloud-n