Front End Engineer (Staff/Senior)

at  Abridge

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.
Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.
We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense.

MUST BE WILLING TO TRAVEL UP TO 10%

Abridge typically hosts a three-day builder team retreat every 3-6 months. These retreats often feature internal hackathons, collaborative project sessions, and social events that allow the team to connect in person.
We value people who want to learn new things, and we know that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.

THE ROLE

We are seeking Staff and Senior Full Stack Engineers to join our growing team! You’ll help us build internal UI products to support LLM Model orchestration, evaluation and dataset curation. You will work closely with our Applied AI and product teams to build innovative ML powered solutions to push the state of the art in Healthcare AI technology.

WHAT YOU’LL DO

• Design, build, and maintain highly scalable, cloud-based services using TypeScript, Python, and React
• Create tooling to support the ML model lifecycle including model evaluations, dataset curation and training infrastructure
• Build scalable infrastructure for LLM model orchestration powered by an intuitive and easy to use user experience
• Make architecture and technology decisions that align with business needs, balancing innovation with security and reliability.
• Enhance our platform’s performance and scalability, with a focus on creating seamless user experiences.
• Work cross-functionally with teams like product, machine learning, and design to ensure the success of new features from conception to deployment.
• Research and evaluate commercial and open-source tools to implement the most effective and scalable solutions.
• Advocate for best coding practices, mentor junior engineers, and ensure the growth of technical excellence across the team.
• Build deep empathy for users, maintaining a user-centric mindset when implementing solutions.
• Contribute to the development and expansion of our ML infrastructure, ensuring smooth interaction between the product and ML models.