Senior Applied AI Engineer

Curai is seeking a Senior Applied AI Engineer to design, build, and ship machine learning and LLM systems that influence how clinicians and patients engage with its healthcare platform. This role covers the full lifecycle, from problem framing and data exploration to training, evaluation, production inference, and measurement of real-world clinical and product impact.

Key Responsibilities

• Lead the technical execution of complex AI initiatives, owning solution design and delivery within a product or technical domain, while collaborating 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, including use cases such as conversational AI, personalization, user understanding, clinical decision support, and chronic care management.
• Own end-to-end problem work: scope with clinicians and product partners, create datasets and evaluations, iterate on modeling, and ship to production with appropriate monitoring and guardrails.
• Develop robust evaluation frameworks, including offline benchmarks, human-in-the-loop review, and online experiments, to support confidence in model safety, accuracy, and ongoing improvement.
• Build and enhance the team’s platform to accelerate delivery, including data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers.
• Partner across clinicians, product, and engineering to translate medical and operational requirements into ML work and deliver measurable improvements to patient and clinician experience.
• Provide technical direction for your area, mentor other engineers, and strengthen engineering and scientific rigor, with leadership scope that increases with seniority.
• Stay current with the literature and the fast-moving AI ecosystem, and bring forward the most relevant ideas for patients and the team.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Math, or a related technical degree.
• 3+ years of hands-on engineering experience, including 1+ years building and deploying machine learning systems with generative AI (LLMs), and a clear track record of impact.
• Strong software engineering fundamentals, with the ability to ship reliable, well-tested Python (or comparable language) code in production.
• Practical knowledge of modern LLM methods, including prompting, retrieval-augmented generation, fine-tuning, and evaluation, plus awareness of their trade-offs.
• Ability to work with messy, real-world data and design evaluations that determine whether a system is actually working.
• Strong written and verbal communication skills, including cross-collaboration with clinicians, product managers, and engineers.
• A bias toward action and ownership, including the ability to take an ambiguous problem to a result and bring others along.
• Motivation to align work with improved health outcomes for real patients.

Technologies

• Python
• LLMs
• Retrieval-augmented generation
• Prompting
• Fine-tuning
• Evaluation

Preferred Qualifications

• 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, including training pipelines, distributed inference, and evaluation platforms, for a small, fast-moving team.
• Track record of technical leadership, such as setting direction across teams, mentoring engineers, or publishing influential work.

Benefits

• High-ownership work on meaningful problems with a tight feedback loop from real clinicians and patients.
• A small, senior team where work shows up in the product quickly.
• Competitive compensation, meaningful equity, and comprehensive benefits.
• Remote-first, flexible work environment across the U.S.
• Comprehensive medical, dental, and vision coverage.
• Flexible spending plans.
• Generous and flexible Paid Time Off (PTO), floating holidays, and parental leave.
• 401k plan with employer matching.
• 100% remote, work from home.

Compensation

USD 175,000 - 200,000 per year. Actual base salary will depend on qualifications and years of relevant experience.

Location

Remote (remote), across the U.S.