Junior Software Engineer

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...

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. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh.

We're looking for early-career Software Engineers who are highly driven and passionate about making a real-world impact through AI for healthcare. You'll join a cross-functional team of researchers, clinicians, and engineers to help translate cutting-edge language model capabilities into dependable clinical systems. You'll be building AI-powered features that touch real clinical workflows, shipping production code, and growing fast in an environment where GenAI is at the center of everything we build.
You will be given an unusual amount of responsibility and autonomy. You will be surrounded by people who want to do their best work. You will experience accelerated learning and career growth. You will have a path to become a future leader of the company. The journey will be demanding but rewarding.
Contribute to backend and frontend systems across Abridge
Shift projects, tackling a wide variety of challenges as you grow and upskill at a startup operating at scale
Collaborate across ML, infrastructure, product, and clinical teams — and develop a genuine understanding of the users and clinicians we serve
Contribute to evaluation frameworks that measure accuracy, robustness, and clinical reliability — including automated pipelines and human-in-the-loop review
Think with an agent-first approach. Continuously learn and relearn agentic coding.
Fine-tune your judgment on where the human in the loop is critical.
Help prototype with new models, prompting techniques, and open-source orchestration tools (LangChain, LlamaIndex, etc.)
Build and iterate on agentic LLM systems — including retrieval pipelines, structured tool use, and chained LLM workflows — as part of a collaborative engineering team
Contribute to monitoring and observability systems that keep our LLM workflows healthy in production
Learn from senior engineers and bring curiosity and fresh perspective to every problem

A degree in CS or a related field, or equivalent experience (projects, bootcamp, open source — we care about what you can build not where you learned it)
Hands-on GenAI experience — through coursework, personal projects, internships, or hackathons. You've integrated an LLM API, built a RAG pipeline, experimented with agents, or shipped something AI-powered and can speak to what you learned
Familiarity with LLM orchestration concepts (prompt chaining, tool use, retrieval) even if you haven't yet used them in a production setting
AI tooling is already part of how you work — you use it to write, debug, and learn faster, and you know when to trust it vs. verify
Curiosity about model evaluation, failure modes, and what it actually takes to make an LLM system reliable
Collaborative, low-ego mindset — we move fast, and we need teammates who pitch in wherever needed
*This role is onsite 5 days a week in our SF office.