Founding Fullstack Engineer

As Founding Fullstack Engineer, you'll be the brain behind Dryft's decision intelligence. You'll build scalable systems that combine agent-based reasoning with mathematical optimization and simulation on top of large-scale industrial data.

Do you have experience in TypeScript?, Do you have a Bachelor's degree?, * Like building scalable, interpretable, data-driven agents from all perspectives - algorithms, architecture and infrastructure.

• Have a strong product sense and enjoy working directly with customers daily
• Have shipped production code end-to-end, are strong in backend & infra and comfortable shipping basic frontend features.
• Have built data-intensive, multi-tenant production systems with Redis, Postgres, and orchestration frameworks. Clickhouse experience is a plus.
• Are ready to work onsite in SF (we support relocation & visa)

TECH STACK

• FE (TypeScript): React, Chakra UI v3, TanStack Router, TanStack Query, Vite
• BE (Python): FastAPI with Pydantic v2, SQLModel, Postgres with pgvector, dagster
• AI: Pydantic AI, Langfuse

• 3 - 5 years of experienceas a fullstack (backend-leaning) engineer with experience at a well known, VC-backed startup.

Pulled from the full job description

• Relocation assistance
• Visa sponsorship, Work Trial at Dryft Office (1/2 to 1 full work day)

Pay: $150,000.00 - $200,000.00 per year

Report tohttps://www.linkedin.com/in/leonie-freisinger/ - Tech stackTypeScript, PythonAbout Dryft Dryft builds intelligent systems that automate complex human decisions in manufacturing operations We're a small, talent-dense team with modest roots and a love for the physical world - cars, machines, planes. Our team includes graduates from Stanford, Berkeley, CDTM, TUM, winners of Stanford TreeHacks, recipients of Fulbright & Haniel scholarships, and builders of everything from robots and race cars to software with millions of downloads. We're backed by the founders and leaders behind Amazon, Facebook, Stripe, Applied Intuition, & others; General Catalyst & Neo, and board members of global industrial companies. Today, we're already saving customers millions. But this is only the beginning. ERPs ran the physical world for half a century. Dryft is powering the next., AJ grew up an internationally competitive ski racer while living hundreds of kilometers away from the alps. Before Dryft, she launched multiple ventures from 0 to 1. In her first full-time job, she founded a new business line for a large engineering firm, securing $3M in contracts within six months. She's helped startups like Kyte scale from the ground up and started her own projects, including a moonshot to develop self-assembling medical devices (backed by Sequoia Partners through Botha Chan) and an educational nonprofit. She also worked in manufacturing at Viessmann and with Siemens' AI Lab on its "factory of the future" initiative. AJ holds an MS in Data Science from Stanford and is an alumna of the Center for Digital Technology & Management (CDTM). At Stanford, she taught flagship entrepreneurship and data science courses, working alongside educators and entrepreneurs such as Steve Blank (4 IPOs), Tina Seelig, and Scott Sandell (NEA). AJ does everything with intensity and loves opposites. She's competed in more than 13 sports and earned numerous scholarships and fellowships (Threshold Venture Fellowship, CEO for One Month, Valedictorian Scholarships, Haniel/Studienstiftung). But her real obsession is with design and detail - from the paint on her 1976 GMC Vandura to the ballgowns she designs herself. Leonie Freisinger [Linkedin], Co-founder & CTO Leonie grew up on her grandparents' farm in southern Germany, where she split her time working on the farm during early mornings and discussing the latest news about machine manufacturers with her family later in the day (her whole family works in those businesses). Before Dryft, she's already been building software for 10+ years: As a sports car engineer at Porsche, she engineered the Taycan's predictive drivetrain controller (now patented). Later, she worked as an ML engineer and did research in time-series forecasting at Stanford, co-developing NeuralProphet (>3M downloads). She led TUM.ai, a 100-person applied-AI team, which is Europe's largest AI student initiative. She completed her master's in ML & Robotics @TUM after studying automotive engineering as an undergraduate, where she graduated valedictorian. Leonie loves to do hackathons (won at Treehacks) and went a full year without skipping a single day of workout. Tech stack- TypeScript, Python