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Salary: USD 175,000 - 210,000 / annual
Curai Health is transforming healthcare delivery by combining advanced AI systems with clinical expertise. This role is a full-stack Senior Software Engineer on the AI engineering team, responsible for designing, building, and shipping machine learning and LLM-based agentic AI workflows that directly impact how clinicians and patients interact with the platform.
You will own complex AI initiatives end-to-end: framing problems with clinicians and product partners, exploring and building datasets, training and evaluating models, productionizing inference systems, and measuring real-world clinical and product impact. Key responsibilities include:
- Lead technical execution of complex AI initiatives, owning design and delivery within a product or technical domain while partnering on broader architectural direction
- Design, build, train, evaluate, and improve advanced ML and LLM-based systems for patient and provider-facing products (conversational AI, personalization, clinical decision support, chronic care management)
- Own problems end-to-end: scope with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with monitoring and guardrails
- Develop robust evaluation frameworks—offline benchmarks, human-in-the-loop review, online experiments—to ensure models are safe, accurate, and improving
- Build and improve platform infrastructure: 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
- Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor
- Stay current with AI literature and ecosystem; bring relevant innovations to the team
The bar is high; this role is for engineers who want significant ownership and thrive where research meets production.
REQUIREMENTS:
- Bachelor's degree in Computer Science, Software Engineering, Math, or related technical field
- 3+ years of hands-on engineering experience with 1+ year building and deploying machine learning systems including generative AI (LLMs), with clear track record of impact
- Strong software engineering fundamentals; ability to ship reliable, well-tested code in Python (or comparable language) in production
- Practical understanding of modern LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and trade-offs
- Comfort working with messy, real-world data and designing evaluations to validate system performance
- Strong written and verbal communication; ability to cross-collaborate with clinicians, product managers, and engineers
- Bias toward action and ownership; ability to take ambiguous problems to results and bring others along
- Mission alignment: commitment to translating work into better health outcomes
NICE TO HAVE:
- Experience applying ML or LLMs in healthcare, life sciences, or other regulated, high-stakes domains
- Clinical NLP, medical knowledge representation, or electronic health record data experience
- Production agentic systems and tool-using LLM experience
- ML infrastructure scaling experience (training pipelines, distributed inference, evaluation platforms)
- Technical leadership track record: cross-team direction-setting, mentoring, or influential publications
