Software Engineer - Early Career

The Role

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.

What You'll Do

• 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 evaluation frameworks that measure accuracy, robustness, and clinical reliability — including automated pipelines and human-in-the-loop review

• Contribute to backend and frontend systems across Abridge

• 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.)

• Contribute to monitoring and observability systems that keep our LLM workflows healthy in production

• Collaborate across ML, infrastructure, product, and clinical teams — and develop a genuine understanding of the users and clinicians we serve

• Learn from senior engineers and bring curiosity and fresh perspective to every problem

What You'll Bring

• 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 either our NYC or SF offices.