21 days ago
Remote, United StatesSenior
Responsibilities
- Lead the architecture, design, and implementation of enterprise AI solutions using LLMs and RAG.
- Design secure, scalable AI architectures and pipelines using Amazon Bedrock and AWS cloud services.
- Define data flows, system interfaces, orchestration, integration patterns, retrieval, vector search, prompt management, and summarization capabilities.
- Establish model selection, retrieval optimization, performance tuning, monitoring, and evaluation strategies for model, prompt, retrieval, and data drift.
- Integrate AI services with enterprise healthcare applications through REST APIs and modern integration patterns.
- Ensure interoperability with FHIR, HL7, and CCD standards and support integration into clinician workflows.
- Incorporate cybersecurity, privacy, Responsible AI, HITL, traceability, data-boundary, retention, explainability, auditability, and governance controls.
- Support ATO, AI governance, Security Impact Analysis, and technology approval activities while protecting PHI and PII.
- Lead 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, technical estimation, and stakeholder presentations.
- Produce architecture documentation, system design artifacts, interface specifications, and implementation guidance.
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 using AWS or comparable cloud platforms.
- Demonstrated experience architecting Artificial Intelligence, Machine Learning, or Generative AI solutions.
- Experience implementing enterprise applications using Amazon Bedrock or similar AI platforms.
- Experience leading technical architecture across multidisciplinary engineering teams.
- Experience with LLMs, RAG, prompt engineering, source-grounded AI evaluation, hallucination testing, vector databases, embeddings, semantic search, REST APIs, enterprise integration, cloud architecture, and distributed systems.
- Knowledge of healthcare interoperability standards including FHIR, HL7, and CCD.
- Knowledge of Responsible AI, NIST AI RMF, NIST SP 800-53, FISMA, FedRAMP, and applicable High-Impact AI requirements.
- Ability to obtain and maintain a Government Public Trust clearance, including required fingerprinting when applicable.
- U.S. citizenship and successful completion of a background check are required.
- Experience with the VA, DoD, or other Federal healthcare organizations is an additional qualification.
- Experience designing AI-enabled clinical workflow, search, summarization, or clinician-support solutions requiring human validation is an additional qualification.
- Familiarity with SNOMED CT, ICD-10, RxNorm, and LOINC is desirable.
- AWS Solutions Architect, AWS AI, Machine Learning, or other AWS cloud certifications are highly desirable.
Benefits
- Medical, dental, and vision insurance.
- 401(k) with employer match.
- Paid time off and Federal holidays.
- Corporate laptop.
- Professional development and training opportunities.
- Remote opportunity.
Tech Stack
Categories
AI ApplicationsSolutions Engineering
