AI​/Machine Learning Solutions Architect

Rare Genomics Institute (RGI) is a nonprofit organization dedicated to helping rare disease patients find a diagnosis, treatment, and pathway to a cure. Through personalized research projects, RGI provides access to world leading medical institutions and scientists to conduct genomic sequencing, coordinates with clinicians and counselors to interpret findings, and offers an online crowd‑funding platform to deliver financial solutions. RGI also supports rare disease advocacy by fostering an online community of rare disease patients and supporting rare disease research through a yearly grant competition.

Since being founded in 2011, RGI has completed over 300 genetic sequencing and analysis projects, assisted patients fund over $3.5 million worth of genomic sequencing, discovered 8 unique genetic mutations in‑house, given over $2 million dollars in grants to researchers on rare disease, and developed an online community with over 10,000 rare disease members. Through volunteers, RGI is able to slowly push science and health care forward to meet the needs of patients affected by rare diseases.

To learn more about RGI, check out our website, like us on Facebook, and follow us on Twitter!

Help make a difference for those living with rare diseases by volunteering with the Rare Genomics Institute (RG). Our non‑profit organization is committed to advocating for rare disease patients by connecting them with next generation sequencing, digital health researchers, cutting‑edge medical devices and knowledge sharing resources. We are working on a project to utilize artificial intelligence (AI) and machine learning (ML) to bring current, scientifically accurate and understandable information on all known rare diseases to our online platforms.

To do this, we are seeking a dedicated, innovative, technically astute AI/ML Solutions Architect to join our team.

This position will be responsible for identifying and implementing artificial intelligence and machine learning solutions in collaboration with our existing project team. The ideal candidate will have a strong background in leveraging generative AI data sources and transitioning them to a user‑friendly website interface. This role will help design the overall end‑to‑end architecture and data flow pipeline for a rare disease chatbot, and guide technology evaluation and selection decisions.

The final output will present medically and scientifically vetted disease information that is understandable to non‑experts. We expect that patients, family members, caregivers, researchers and those simply interested in specific rare diseases will utilize this information to understand and cope with rare conditions, and to learn about causes and treatment strategies. We will provide this service free of charge and open to all.

• Strategic thinker with leadership and communications skills to work with cross‑functional teams and any direct reports.
• Experience with LLM, RAG and vector databases to create advanced generative AI prompts to obtain relevant data from multiple sources and consolidating the information to identify and remove inaccuracies.
• Deep AI/ML systems knowledge with proven experience designing and deploying AI/ML solutions or products, preferably in SaaS (software as a service), healthtech, or similar areas.
• Experience with AI development tools and frameworks such as Python, Tensor Flow, PyTorch, Hugging Face, or similar.
• Experience with front‑end/back‑end integration of AI models, especially for delivering accessible, plain‑language content to lay audiences.

• Drive the development and implementation of a technically‑sound strategy for the creation of the RG rare disease AI information platform.
• As needed, reach out and engage with external collaborators or resources to support project objectives.
• Working with the project team, identify key tasks, timelines and final objectives.
• Attend bi‑weekly team meetings and regularly engage with team members remotely.
• Ensure that final products comply with data ethics, security, and medical domain knowledge standards to ensure trust and accuracy.