About Iollo

iollo is a Stanford-founded startup. We've built Quinn, an AI scientist that compresses drug discovery from years to days, and a blood testing platform analyzing 600+ biomarkers for medical practices nationwide. We need an engineer to own the infrastructure powering both products.

Scientific research typically takes months or years - limited by human bandwidth. The engineering challenge: build infrastructure that allows Quinn to access diverse scientific data formats, run complex analysis at scale, and operate securely inside pharma companies' own environments. You'll also own the blood testing platform infrastructure - from sample processing workflows to results delivery. You'll architect both systems while working directly with our Stanford scientists.

What Makes This Role Different

Build infrastructure for an AI that performs months of scientific analysis in hours Your code will directly impact scientific discovery timelines Process large biomedical datasets and turn them into actionable insights Work on AI for scientific discovery - not just another chatbot application

Responsibilities

Own the complete technical architecture enabling our AI scientist to run secure analyses in enterprise environments Own the complete implementation across frontend, backend, and infrastructure for our blood testing platform Design event-driven systems that orchestrate complex scientific workflows Build infrastructure that lets AI analyze biomedical data at the scale of 20+ person research teams Implement LLM architectures for scientific analysis and discovery Create data pipelines that handle biomedical data Ensure HIPAA/SOC2/ISO27001-compliant deployments for pharma and biotech partners Partner with Stanford scientists to translate research into production systems Scale platforms that serve both startups and Fortune 500 companies Take on additional technical challenges as we grow and evolve our products

Our current tech stack includes

Infrastructure: AWS (Lambda, ECS, Fargate, S3, App Runner, Cognito, Aurora PostgreSQL, SQS), deployed via AWS CDK/Terraform Backend: Node.js, Nest.js, Python (for AI/ML services) Frontend: React, TypeScript, Tailwind, deployed on Vercel Databases: PostgreSQL, MongoDB, Redis Architecture: Event-driven microservices, serverless functions

What You'll Need

3+ years shipping production code as a full-stack engineer with high ownership mentality Strong AWS and event-driven architecture experience - you know how to build systems that scale Expertise in Node.js/Nest.js and React - you can build performant applications Python experience for AI/ML services Track record of architecting systems from zero to production Experience with LLM integration - you understand the potential and limitations of AI Comfortable processing data at scale - including large biomedical files Self-directed - you identify and solve problems independently Infrastructure as code experience (Terraform/CDK) Interest in using AI to accelerate scientific discovery

Nice to have

Experience with HIPAA compliance and healthcare data security Familiarity with biomedical data formats and standards Background with real-time data processing systems

Why join us

Help discover new science while bringing treatments to market faster through your work Build for an AI that performs analysis equivalent to teams of scientists Join at an ideal stage: established pharma customers with significant growth ahead Work on complex technical challenges at the intersection of AI and biology Shape the foundation of products already in use by partners Direct collaboration with Stanford scientists Competitive compensation with meaningful equity Health Care Plan and hybrid work

If you're excited about this role but your experience doesn't align perfectly with every requirement, we still want to hear from you. We value diverse perspectives and are looking for engineers who are passionate about solving hard problems at the intersection of AI and science. #J-18808-Ljbffr