at Thoughtful AI · 101-250 employees
Thoughtful.ai builds role-based AI agents and an automation platform that uses LLMs, NLP, OCR, and RPA to automate healthcare revenue-cycle tasks such as claims processing, eligibility verification, and payment posting.
<div class="content-intro"><p>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 <span><a href="http://smarterdx.com/careers" target="_blank">smarterdx.com/careers</a></span>.</p></div><p><strong>Role</strong></p> <p>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.<br><br>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.<br><br>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.</p> <p><em>**This role is fully remote within the US**</em></p> <p><strong>What You’ll Do</strong></p> <ul> <li>Design, build, and launch backend services and product capabilities that incorporate LLMs, machine learning models, and other AI systems</li> <li>Build production-grade workflows around model inference, structured outputs, tool use, retrieval, agentic workflows, and other LLM application patterns</li> <li>Partner closely with Data Scientists to take models and experimental approaches from exploration into reliable, maintainable production systems</li> <li>Develop evaluation, observability, and feedback mechanisms to understand and improve AI system performance in production</li> <li>Design systems that gracefully handle the probabilistic and non-deterministic behavior of AI models</li> <li>Work with clinical and operational data across structured and unstructured formats, including documents and images</li> <li>Collaborate across engineering, product, data science, and clinical disciplines to understand users and rapidly iterate on new ideas</li> <li>Design and improve the backend architecture that supports SmarterDx’s applications at scale</li> <li>Protect patients’ privacy and security through secure coding and data-handling practices</li> <li>Research and advocate for improved techniques, architectures, and development practices as the applied AI ecosystem evolves</li> <li>Support SmarterDx’s applications and AI systems in production</li> </ul> <p><strong>What You Bring</strong></p> <ul> <li>5+ years of software development experience, with significant experience building backend and cloud-based systems</li> <li>Expertise in Python and/or TypeScript, with strong software engineering fundamentals</li> <li>Experience building LLM-powered applications that have been deployed to production</li> <li>Experience integrating models into larger software systems rather than working exclusively on model training or ML infrastructure</li> <li>Experience collaborating closely with Data Scientists, Machine Learning Engineers, or research-oriented teams</li> <li>Experience designing APIs, services, data models, and asynchronous or event-driven workflows</li> <li>Experience working with Postgres or a similar relational database</li> <li>Experience building cloud-native distributed systems</li> <li>Familiarity with evaluating, debugging, and monitoring AI systems in production</li> <li>Strong judgment around reliability, testing, observability, and failure handling in systems that incorporate probabilistic model outputs</li> <li>Experience working in a security-conscious environment</li> <li>Excellent communication and cross-functional collaboration skills</li> <li>Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent experience</li> </ul> <p><strong>Nice To Haves</strong></p> <ul> <li>Experience with both traditional machine learning models and modern generative AI / LLM applications</li> <li>Experience with LLM application frameworks or orchestration tools such as LangChain or LangGraph</li> <li>Experience with LLM observability and evaluation platforms such as Langfuse, Braintrust, or similar tools</li> <li>Experience building retrieval-augmented generation, tool-calling, agentic, or multi-step AI workflows</li> <li>Experience with computer vision, multimodal models, document understanding, or OCR pipelines</li> <li>Experience designing evaluation datasets, automated evaluations, human-in-the-loop workflows, or model feedback loops</li> <li>Experience at a scale-up or rapid-growth technology company</li> <li>Experience in health tech, particularly with clinical data or hospital billing systems</li> <li>Experience working with Kubernetes</li> <li>Experience with HL7 / FHIR and other EHR-related technologies</li> <li>Experience with Snowflake</li> <li>Experience with Datadog</li> </ul> <p><strong>Our Stack</strong></p> <p>Python, TypeScript, React, Kubernetes, Postgres, DBOS, AWS, Terraform, Snowflake, Datadog, Braintrust, EasyLLM</p> <p><strong>Compensation</strong></p> <p>$190K t