Gamma Venture Studio is helping to recruit for this role. We will conduct the screening interview and if you meet the requirements, then we will submit you to the hiring manager at the hiring company.
Hiring for 2 similar roles: Founding Fullstack Engineering Role at Dryft, One Founding Role and the Infrastructure Engineer at Kaizen
Dryft- Founding Fullstack Engineer- Full-timeOn-site- San Francisco- $150K - $250K(Based on qualifications and experience)
Kaizen- Infrastructure Engineer- Full-time, On-site in San Francisco, CA Salary $185K - $235K
About the Dryft role
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.
YOU
- 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.
- Salary$150K - $250K (Based on qualifications and experience)
- EquityCompetitive equity
- Visa sponsorship available and relocation support available
- On-site work policy- 6 days in-office (Sun-Fri) in San Francisco, CA. Full-time
- 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.
Team size 8 employees
Founded2025
Website- dryft.ai/
Total funding$5M
About the team
Anna-Julia Storch [Linkedin], Co-Founder & CEO
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
Interview process
Phone Screening Interview with Gamma Venture Studio, will pass on to hiring Manager if meets requirements
Initial Screen (15 mins) with Hiring Manger
Code interview (30-60 mins)
Work Trial at Dryft Office (1/2 to 1 full work day)
Kaizen- About the Infrastructure Engineering role
What we're looking for:
We need someone with 5-12 years of experience operating production cloud infrastructure end-to-end who has strong Terraform and GCP/AWS expertise. You should be comfortable building infrastructure from scratch at a fast-moving early-stage startup and have a track record of shipping reliable, scalable systems with high autonomy. Bonus points if you've worked in AI/ML-adjacent environments or have deep GCP experience (GKE, Cloud SQL, Artifact Registry).
What you'll do:
- Design and build production cloud infrastructure from the ground up — including networking, IAM, secrets management, and container orchestration
- Take ownership of Terraform modules and IaC workflows end-to-end, reasoning carefully about blast radius and failure modes
- Work closely with a small, highly technical founding team (reporting directly to the CTO) to architect infrastructure that supports rapidly scaling RL environments for agentic AI
- Build and maintain CI/CD pipelines and release processes that ship software reliably and stop broken changes before production
- Stand up and manage PostgreSQL databases from scratch — schema design, migration strategy, and production-scale operations
- Design and implement observability stacks (logs, metrics, traces) so the team can diagnose and resolve incidents quickly
- Future-proof platform infrastructure as AI capabilities evolve on a 3-month cadence, building beyond just servicing today's demand
- 5 - 12 years of experience, years operating production cloud infrastructure end-to-end
- Salary$185K - $235K + Equity0.25% - 0.5%
Visa sponsorship available- Kaizen will sponsor any visa type for the right candidate.
- On-site work policy, In-person at Kaizen's San Francisco office. The team works together in-office daily. Full-time position, LocationSan Francisco, CA
- Report to https://www.linkedin.com/in/mscornavacca/
- Tech stackGCP, Terraform, Kubernetes, GKE, Docker, PostgreSQL, Cloud SQL, CI/CD, Prometheus, Grafana, Datadog, OpenTelemetry, Alembic, Atlantis, Cloud Build, Artifact Registry, Auth0, OIDC, AWS
About Kaizen
Kaizen builds reinforcement learning environments that enable AI to train from its own experience instead of being limited by human-labeled data, solving the core infrastructure bottleneck toward autonomous agentic AI systems.
Team size 6 employees
Founded2025
About the team
Kaizen is a team of six, built from a tight-knit group of friends and classmates from Princeton, Harvard, and Dartmouth — all technical, all builders. Four of the six were classmates at Princeton, and the team came together through deep personal trust: the founder recruited his former college co-founder CTO (who had gone to Meta post-grad), who then brought on the smartest technical person he knew, and so on.
What makes this team unique is the combination of elite technical ability and genuine friendship. Everyone is an engineer. Everyone ships code. The CTO is 24. The team skews young, moves fast, and actually enjoys spending time together beyond the demands of startup life.
The culture is high-agency, low-bureaucracy, and deeply collaborative — no silos, no layers of management. Everyone works on everything, and the expectation is that any team member could be dropped into an unfamiliar stack and ramp within weeks. If you thrive on autonomy, want to work alongside people who've been operating at the highest technical level since college, and value a team that's as fun to grab lunch with as it is to whiteboard with — that's Kaizen.
Tech stackGCP, Terraform, Kubernetes, GKE, Docker, PostgreSQL, Cloud SQL, CI/CD, Prometheus, Grafana, Datadog, OpenTelemetry, Alembic, Atlantis, Cloud Build, Artifact Registry, Auth0, OIDC, AWS
The Product
Kaizen builds reinforcement learning (RL) environments specifically designed for computer use, enabling AI models to train themselves through direct interaction with the digital world — clicks, scrolls, and key presses — rather than relying on human-labeled data. The platform provides the core infrastructure that allows frontier AI labs to put their models into realistic digital environments where they can learn from their own experience. This solves a fundamental bottleneck in developing autonomous agentic AI systems: the scarcity and cost of human-generated training data. Kaizen's environments let AI models: Train by actually navigating and interacting with software interfaces. Improve continuously through self-generated experience rather than static datasets. Develop genuine computer-use capabilities at scale. The company sells these environments directly to AI labs at the frontier, providing both custom environment architecture for specific use cases and a broader platform that scales across customers. As AI capabilities evolve on a roughly three-month cadence, Kaizen is building future-proof infrastructure that stays ahead of rapidly shifting model capabilities.
Interview process
-Screening Phone/Audio Interview with Gamma Venture Studio and if you meet the requirements then I submit your profile to the hiring manager and If they decide to proceed then I will reach out to you
- Initial Screen with Company(Optional) (30 minutes)
- Technical Screen (1 hour)
- Final Onsite (Superday) (3-4 hours)
Pay: $185,000.00 - $235,000.00 per year
Work Location: In person
Pay: $150,000.00 - $250,000.00 per year
Benefits:
Application Question(s):
- Are you more interested in the founding role or Infrastructure Role?
- Have you ever worked at a Startup and do you have founding Engineer Experience?
Work Location: In person
