高级AI应用工程师（远程机会）
Senior AI Application Engineer (Remote Opportunity)
VetsEZ 正在寻找一名高级 AI 应用工程师，负责设计、开发和实施支持美国退伍军人事务部（VA）的企业级人工智能（AI）解决方案。初始任务将支持联合纵向查看器（JLV）AI 生成摘要项目，在经批准的测试环境中利用检索增强生成（RAG）、大语言模型（LLMs）和 Amazon Bedrock，提供安全、受控的 AI 辅助搜索和摘要功能，同时支持临床评估和未来生产就绪性。
与 AI 解决方案架构师、产品负责人、网络安全团队、DevSecOps 工程师和临床利益相关者紧密合作，该职位将开发安全、可扩展且易于维护的 AI 驱动应用，无缝集成到现有企业医疗系统中，同时确保符合联邦安全、隐私和 AI 治理要求。
职责：
- 利用大语言模型（LLMs）和检索增强生成（RAG）设计、开发和实现企业级 AI 应用。
- 使用 Amazon Bedrock 开发 AI 辅助搜索、摘要和问答功能。
- 构建可重用的 AI 服务，支持提示编排、文档检索和响应生成。
- 实现提示工程和来源锚定策略，以提高 AI 的准确性、一致性、可追溯性和临床相关性，包括支持人工验证的来源链接。
- 在响应质量、延迟和运营成本之间取得平衡，优化 AI 性能。
- 设计和开发安全、可扩展的云原生应用，使用现代软件工程实践。
- 开发 RESTful API 和后端服务，支持 AI 功能和企业集成。
- 在选定的患者上下文和 CHSD 文档集内实现经批准的文档检索、向量搜索和语义搜索功能。
- 开发自动化单元测试、集成测试和功能测试，以及可重复的 AI 评估，用于评估基础性、检索质量和临床相关性，支持 AI 驱动的应用。
- 排查软件缺陷，优化应用性能，并支持经批准的测试环境内的活动及未来生产就绪性。
- 将 AI 功能集成到现有的企业医疗应用和临床工作流程中。
- 开发安全接口，使用 REST API 和现代集成平台
查看英文原文
VetsEZ is seeking a Senior AI Application Engineer to design, develop, and implement enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA). The initial assignment will support the Joint Longitudinal Viewer (JLV) AI Summarization initiative, delivering a secure, governed AI-assisted search and summarization capability within an approved test environment utilizing Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Amazon Bedrock, while supporting clinical evaluation and future production readiness.
Working closely with AI Solution Architects, Product Owners, cybersecurity teams, DevSecOps engineers, and clinical stakeholders, this individual will develop secure, scalable, and maintainable AI-powered applications that integrate seamlessly with existing enterprise healthcare systems while ensuring compliance with Federal security, privacy, and AI governance requirements.
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.
- Support CI/CD pipelines, automated deployments, and cloud-native operational practices.
- 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.
- Ability 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.
Benefits:
- Medical, Dental, and Vision Insurance
- 401(k) with Employer Match
- Paid Time Off plus Federal Holidays
- Corporate Laptop
- Professional Development and Training Opportunities
- Remote Opportunity
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.
Sorry, we are unable to offer sponsorship at this time.
Originally posted on Himalayas