Senior Software Engineer, Agentic AI - Curai Health

At Curai, we believe that access to high-quality healthcare is a fundamental human right, not a privilege. Our mission is to radically transform healthcare delivery by harnessing the power of artificial intelligence and clinical expertise to make care more affordable, accessible, and effective for everyone. Patients interact with advanced AI systems at every step of their care and follow-up, with licensed physicians reviewing each case for clinical decisions in our integrated virtual clinic.

We are hiring a Full-Stack Senior Software Engineer to push the frontier of agentic and applied AI in healthcare. As a member of the technical staff on the artificial intelligence engineering team, you will design, build, and ship ML and LLM systems (agentic AI workflows) that directly shape how clinicians and patients interact with our platform.

What You'll Do

• Lead the technical execution of complex AI initiatives, owning the design and delivery of solutions within a product or technical domain while partnering with senior engineers on broader architectural direction.
• Design, build, train, evaluate, and improve advanced machine learning and LLM-based systems for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management).
• Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails.
• Develop robust evaluation frameworks—offline benchmarks, human-in-the-loop review, online experiments—that ensure our models are safe, accurate, and improving over time.
• Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers.
• Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience.
• Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor.
• Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.

What You'll Bring

• Bachelor’s degree in Computer Science, Software Engineering, Math, or a related technical field.
• 3+ years of hands-on engineering experience with 1+ year building and deploying machine learning systems including generative AI (LLMs), and a clear track record of impact.
• Strong software engineering fundamentals and the ability to ship reliable, well-tested code in Python (or a comparable language) in a production environment.
• Practical understanding of modern LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and the trade-offs between them.
• Comfort working with messy, real-world data and designing evaluations to verify system performance.
• Strong written and verbal communication skills; ability to cross-collaborate with clinicians, product managers, and engineers across disciplines.
• A bias toward action and ownership: ability to take an ambiguous problem, drive it to a result, and bring others along.
• Passion for the mission to translate work into better health outcomes for real patients.

Nice to Have

• Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain.
• Experience with clinical NLP, medical knowledge representation, or working with electronic health record data.
• Experience building agentic systems and tool-using LLMs in production.
• Experience scaling ML infrastructure—training pipelines, distributed inference, evaluation platforms—for a small, fast-moving team.
• Track record of technical leadership: setting direction across teams, mentoring engineers, or publishing influential work.

What We Offer

• High ownership work on problems that matter, with a tight feedback loop from real clinicians and patients.
• A small, senior team where your work shows up in the product quickly.
• Competitive compensation, meaningful equity, and comprehensive benefits.
• Remote-first, flexible work environment across the U.S.