高级软件工程师，后端（应用AI）
Senior Software Engineer, Backend (Applied AI)
SmarterDx 正在改变医疗系统使用临床 AI 的方式，以实现患者护理的全部价值。我们的临床 AI 平台由医生-数据科学家打造，并基于经过临床验证的电子健康记录数据进行训练，能够解读每个患者故事背后的细微差别，并为收入周期团队提供临床合理的建议——帮助医院追回应得收入，提高质量指标，减少拒付，简化收入周期运营。作为 Smartian，你将参与构建让每个人都能更准确、可持续和高效地使用医疗的技术。了解更多请访问 [smarterdx.com/careers](http://smarterdx.com/careers)。
**职位**
我们正在寻找一位具有应用 AI 经验的后端导向高级软件工程师，帮助构建支撑 SmarterDx 临床 AI 产品的系统。
该职位位于后端工程、机器学习和产品开发的交汇点。你将构建结合传统软件系统与机器学习，以及日益增长的 LLM 驱动功能的生产级应用。你将与数据科学家和其他产品工程师紧密合作，将模型、实验和新兴 AI 技术转化为由医疗团队使用的可靠产品体验。
理想的候选人具备扎实的后端工程基础，并且之前曾构建和运行过 LLM 密集型的生产级应用。你不需要是 ML 基础设施专家，但你应该能够直接与模型协作，理解它们的行为和限制，并围绕它们设计应用架构。拥有传统机器学习经验是有价值的，特别是如果你最近有在 LLM、多模态模型或其他现代 AI 系统驱动的应用上工作的经验。
_**该职位在美国境内完全远程办公**_
**你将负责**
- 设计、构建并发布包含 LLM、机器学习模型和其他 AI 系统的后端服务和产品功能
- 构建围绕模型推理、结构化输出、工具使用、检索、代理工作流等 LLM 应用模式的生产级工作流
- 与数据科学家紧密合作，将模型和实验方法从探索阶段转化为可靠、可维护的生产系统
- 开发评估、可观测性和反馈机制，以理解和提升生产环境中的 AI 系统性能
- 设计系统以优雅地处理概率性和非确定性因素
查看英文原文
SmarterDx is transforming how health systems use clinical AI to capture the full value of patient care delivered. Built by physician-data scientists and trained on clinically-validated EHR data, our clinical AI platform interprets the nuances behind every patient story and makes clinically-sound recommendations for revenue cycle teams — helping hospitals recover earned revenue, improve quality metrics, reduce denials, and streamline revenue cycle operations. As a Smartian, you’ll help build technology that makes healthcare more accurate, sustainable, and effective for everyone. Learn more at [smarterdx.com/careers](http://smarterdx.com/careers).
**Role**
We are looking for a backend-oriented Senior Software Engineer with applied AI experience to help build the systems that power SmarterDx’s clinical AI products.
This role sits at the intersection of backend engineering, machine learning, and product development. You’ll build production applications that combine traditional software systems with machine learning and increasingly LLM-driven capabilities. You’ll work closely with Data Scientists and other Product engineers to turn models, experiments, and emerging AI techniques into reliable product experiences used by healthcare teams.
The ideal candidate has strong backend engineering fundamentals and has previously built and operated LLM-heavy applications in production. You don’t need to be an ML infrastructure specialist, but you should be comfortable working directly with models, understanding their behavior and limitations, and designing the application architecture around them. Experience with traditional machine learning is valuable, particularly if you have more recently worked on applications powered by LLMs, multimodal models, or other modern AI systems.
_**This role is fully remote within the US**_
**What You’ll Do**
- Design, build, and launch backend services and product capabilities that incorporate LLMs, machine learning models, and other AI systems
- Build production-grade workflows around model inference, structured outputs, tool use, retrieval, agentic workflows, and other LLM application patterns
- Partner closely with Data Scientists to take models and experimental approaches from exploration into reliable, maintainable production systems
- Develop evaluation, observability, and feedback mechanisms to understand and improve AI system performance in production
- Design systems that gracefully handle the probabilistic and non-deterministic behavior of AI models
- Work with clinical and operational data across structured and unstructured formats, including documents and images
- Collaborate across engineering, product, data science, and clinical disciplines to understand users and rapidly iterate on new ideas
- Design and improve the backend architecture that supports SmarterDx’s applications at scale
- Protect patients’ privacy and security through secure coding and data-handling practices
- Research and advocate for improved techniques, architectures, and development practices as the applied AI ecosystem evolves
- Support SmarterDx’s applications and AI systems in production
**What You Bring**
- 5+ years of software development experience, with significant experience building backend and cloud-based systems
- Expertise in Python and/or TypeScript, with strong software engineering fundamentals
- Experience building LLM-powered applications that have been deployed to production
- Experience integrating models into larger software systems rather than working exclusively on model training or ML infrastructure
- Experience collaborating closely with Data Scientists, Machine Learning Engineers, or research-oriented teams
- Experience designing APIs, services, data models, and asynchronous or event-driven workflows
- Experience working with Postgres or a similar relational database
- Experience building cloud-native distributed systems
- Familiarity with evaluating, debugging, and monitoring AI systems in production
- Strong judgment around reliability, testing, observability, and failure handling in systems that incorporate probabilistic model outputs
- Experience working in a security-conscious environment
- Excellent communication and cross-functional collaboration skills
- Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent experience
**Nice To Haves**
- Experience with both traditional machine learning models and modern generative AI / LLM applications
- Experience with LLM application frameworks or orchestration tools such as LangChain or LangGraph
- Experience with LLM observability and evaluation platforms such as Langfuse, Braintrust, or similar tools
- Experience building retrieval-augmented generation, tool-calling, agentic, or multi-step AI workflows
- Experience with computer vision, multimodal models, document understanding, or OCR pipelines
- Experience designing evaluation datasets, automated evaluations, human-in-the-loop workflows, or model feedback loops
- Experience at a scale-up or rapid-growth technology company
- Experience in health tech, particularly with clinical data or hospital billing systems
- Experience working with Kubernetes
- Experience with HL7 / FHIR and other EHR-related technologies
- Experience with Snowflake
- Experience with Datadog
**Our Stack**
Python, TypeScript, React, Kubernetes, Postgres, DBOS, AWS, Terraform, Snowflake, Datadog, Braintrust, EasyLLM
**Compensation**
$190K to $230K base salary
_#LI-DNI_
#### Benefits
- **Medical, Dental & Vision** – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- **Paid Parental Leave** – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- **Remote-First Team** – Work from anywhere in the U.S.
- **Unlimited PTO & 11 Holidays** – So you can relax and recharge.
- **401(k) with Traditional & Roth Options**– Tax-advantaged retirement savings through Fidelity with a 4% match.
- **Minimal Bureaucracy** – A fast-moving, high-impact environment where you can focus on what matters.
- **Incredible Teammates!** – Work alongside smart, supportive, and mission-driven colleagues.