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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 . 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.