Full Stack Engineer, LLM APIs (Staff/Senior)

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.

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.

What You'll Bring

• 5+ years of experience building and scaling distributed systems using modern technologies like TypeScript, Python, React, and Node.js

• Hands-on experience integrating and working with Large Language Models (LLMs) and APIs, with familiarity in fine-tuning and prompt engineering

• Proficiency in working with cloud services (AWS, GCP), infrastructure as code (Terraform), and containerization (Docker, Kubernetes)

• Proven experience leading engineering teams or owning major software components from development to production

• A background in optimizing and scaling inference systems for LLMs or similar AI-based systems is highly desirable

• Experience working in regulated environments (HIPAA, SOC 2, or HITRUST) is a plus

• A passion for learning new technologies and sharing knowledge within your team

Base Salary: $185,000 USD - $265,000+ USD per year + Equity

The salary range provided is based on transparent pay guidelines and is an estimate for candidates residing in the San Francisco and New York City metro areas. The actual base salary will vary depending on the candidate's location, relevant experience, skills, qualifications, and other job-related factors. Additionally, this role may include the opportunity to participate in a company stock option plan as part of the total compensation package.

Must be willing to work from our SF or NYC office at least 3x/week (Relocation assistance is available for candidates willing to move to San Francisco or New York)

Strong preference for candidates who are currently in the San Francisco Bay Area or the New York Tri-State area, or are willing to relocate to these areas. This position requires a commitment to a hybrid work model, with the expectation of coming into the office 2-3 times per week.

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.

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