Senior AI Application Engineer (Remote Opportunity)

Responsibilities

• Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
• Develop AI-assisted search, summarization, and question-answering capabilities using Amazon Bedrock.
• Build reusable AI services supporting prompt orchestration, document retrieval, and response generation.
• Implement prompt engineering and source-grounding strategies to improve AI accuracy, consistency, traceability, and clinical relevance, including source links that support human verification.
• Optimize AI performance while balancing response quality, latency, and operational cost.
• Design and develop secure, scalable cloud-native applications utilizing modern software engineering practices.
• Develop RESTful APIs and backend services supporting AI capabilities and enterprise integrations.
• Implement approved document retrieval, vector search, and semantic search capabilities within the selected patient context and CHSD document set.
• Develop automated unit, integration, and functional tests and repeatable AI evaluations for groundedness, retrieval quality, and clinical relevance supporting AI-enabled applications.
• Troubleshoot software defects, optimize application performance, and support activities within the approved test environment and for future production readiness.
• Integrate AI capabilities into existing enterprise healthcare applications and clinical workflows.
• Develop secure interfaces utilizing REST APIs and modern integration patterns.
• Support interoperability utilizing healthcare standards including FHIR, HL7, and CCD.
• Collaborate with Solution Architects and engineering teams to implement scalable and maintainable application designs.
• Participate in code reviews and promote software engineering best practices across the development team.
• Develop secure software in accordance with Federal cybersecurity and privacy requirements, including approved data-retention and purge controls.
• Implement logging, monitoring, audit capabilities, and operational telemetry, including model and prompt version tracking, usage and cost monitoring, and controls to detect model, prompt, retrieval, and data drift.
• Support application security scanning, vulnerability remediation, and activities within the approved test environment and for future production readiness.
• Incorporate Responsible AI, Human-in-the-Loop (HITL), and AI governance principles into application development.
• Collaborate with architects, product owners, clinicians, cybersecurity teams, and Government stakeholders throughout the software development lifecycle.
• Participate in Agile ceremonies including Sprint Planning, backlog refinement, Sprint Reviews, and Retrospectives.
• Contribute to technical documentation, implementation guides, and software design artifacts.
• Present technical solutions and implementation approaches to project 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.
• 8+ years developing enterprise software applications.
• 5+ years developing cloud-native applications utilizing AWS or comparable cloud platforms.
• Demonstrated experience developing Artificial Intelligence, Machine Learning, or Generative AI solutions.
• Experience implementing applications utilizing Amazon Bedrock or similar enterprise AI platforms.
• Experience developing enterprise REST APIs and cloud-native application services.
• Amazon Bedrock and AWS cloud services
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Prompt engineering and AI evaluation
• Python, Java, or C#
• REST APIs and JSON
• Vector databases, embeddings, and semantic search
• Git, CI/CD, and DevSecOps
• Healthcare interoperability (FHIR, HL7, CCD)

Additional Qualifications

• Strong understanding of modern software engineering principles and cloud-native application development.
• Experience developing scalable, secure, and maintainable enterprise applications.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong written and verbal communication skills with the ability to collaborate across multidisciplinary engineering teams.
• Able to obtain and maintain a Government Public Trust clearance.
• Experience supporting the Department of Veterans Affairs (VA), Department of Defense (DoD), or other Federal healthcare organizations.
• Experience developing AI-enabled clinical workflow, information-retrieval, or clinician-support applications requiring human validation.
• Experience implementing vector search, embeddings, semantic search, and prompt orchestration.
• Knowledge of Responsible AI, NIST AI Risk Management Framework (AI RMF), NIST SP 800-53, FISMA, and FedRAMP.
• Familiarity with clinical terminology standards including SNOMED CT, ICD-10, RxNorm, and LOINC.
• AWS Developer, AWS AI, Machine Learning, or other AWS cloud certifications are highly desirable.