Forward Deployment Engineer (Residency Program)
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 14, 2026. Hippocratic AI scores B on the Alion truth index.
Join HAI as a Forward Deployed Engineer (FDE) Resident, where you'll be responsible for delivering safe, autonomous clinical conversations with patients. You'll develop and refine conversation logic, architect data integration, and collaborate with clinicians to improve patient experience. This role offers a unique opportunity to make a lasting impact in the healthcare industry.
Missions
- Assurer la livraison de conversations cliniques autonomes et sûres avec les patients, en développant et en affinant les invites et la logique de conversation.
- Architecturer les transports et les mappages pour intégrer les données dans et hors de ces conversations.
- Collaborer avec des cliniciens, des chefs de produit et des ingénieurs pour traduire les exigences cliniques en conceptions de conversation.
Profil recherché
- Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field (or equivalent demonstrated coursework and professional projects)- Experience building integrations with databases and RESTful APIs, including understanding of async patterns and error handling
- Strong problem-solving mindset with proven ability to break down complex problems and iterate toward solutions
- 2+ years of professional industry experience in software development, AI/ML, or related technical roles
- Demonstrated experience with LLM prompting through professional work or substantial personal projects (ChatGPT, Claude, or similar models)
- Strong Python proficiency with hands-on experience writing production or near-production code
- Experience with backend development frameworks (Flask, Django, FastAPI, Spring Boot, or similar)
- Portfolio of personal or academic projects demonstrating full-stack development, AI experimentation, or prompt engineering work
- Understanding of data privacy, security, and compliance best practices, particularly in regulated healthcare environments (HIPAA, healthcare data handling)
- Familiarity with AI/ML concepts including model architectures, training approaches, or evaluation methods
- Healthcare or health-tech experience, including exposure to clinical workflows, EHR systems, or patient-facing applications
- Experience with prompt engineering frameworks or tools (LangChain, LangSmith, Anthropic SDK, etc.)