AI Systems Engineering Intern
We are hiring a founding AI Systems Engineering Intern to work directly with the Stanford founding team on designing and building the core platform architecture for our stealth AI startup. You will not be assigned isolated tickets; you will help architect, build, and ship the core system.
This role is ideal for someone who
- Builds full-stack projects independently
- Think in systems, not features
- Wants to build something used by governments and major enterprises
- Thrives in ambiguity
What You'll Build
- Multi-tenant Saas backend architecture
- AI-driven documentation ingestion pipelines (PDF, Excel, contracts)
- Risk scoring and anomaly detection modules
- Vector search + structured extraction workflows
- Role-based access control systems
- Audit logging frameworks
Required Technical Skills
- Core Engineering
- Strong Python (FastApp/Django preferred)
- TypeScript (Node.js/Next.js/React)
- REST API design
- Database Schema design (Postgres)
- Git proficiency
- AI integration
- Experience using LLM APIs (OpenAI/Anthropic)
- Building structured extraction pipelines
- Embeddings + retrieval systems
- Evaluation loops for model reliability
- Data Engineering
- Parsing messy structured/unstructured data
- ETL pipeline design
- Reproducible workflows
- Data versioning concepts
Bonus Skills
- AWS deployment experience
- Docker
- Background jobs (celery/queues)
- Security fundamentals (JWT, OAuth, encryption basics)
- Experience shipping a production Saas app
- Experience in Fintech, govtech, or infrastructure domains
Qualifications
- MS student in Computer Science
- Exceptional upperclassmen with substantial technical experience considered
- 1–2 years of industry or applied ML experience preferred