Principal Software Engineer

About Us

We’re a stealth-stage, venture-backed TechBio startup on a mission to transform regenerative medicine using large-scale AI. Backed by $60M in Series A funding from top investors and advised by pioneers from MIT, Harvard, and the biotech world, our team is building a foundation model that redefines how human cell types are created and controlled.

Our proprietary technology allows us to generate biological data 1,000x more efficiently than current methods, unlocking a new paradigm in cellular engineering. We’re not iterating on existing science — we’re rebuilding the toolkit for cell therapy from the ground up using deep learning, massive-scale experimentation, and cutting-edge software systems.

We’ve assembled a world-class founding team with previous exits worth over $1B and experience spanning AI, systems engineering, and developmental biology. This is your opportunity to be a core engineering partner as we build the infrastructure to support what we believe will be the AlphaFold moment for stem cell biology.

Responsibilities

As a Principal Software Engineer, you’ll be one of the first core engineering hires, working across the stack to architect and scale systems that connect biology, machine learning, and high-throughput data generation. You’ll play a critical role in:

Designing and building robust, scalable infrastructure to support AI-driven experimentation and protocol discovery.

Developing intuitive internal tools and visualization interfaces to empower scientists and ML researchers.

Collaborating closely with wet-lab biologists, ML engineers, and platform teams to define requirements and deliver production-grade software.

Taking projects from 0-to-1: identifying technical gaps, defining architecture, and delivering solutions quickly in a fast-moving environment.

Contributing to the cultural and technical foundation of the engineering team as we scale.

Qualifications

Must-Have:

7+ years of experience in backend, infrastructure, or full-stack engineering roles.

Strong fluency in Python and modern software engineering practices (CI/CD, testing, containerization, cloud infra).

Experience building and scaling data pipelines, APIs, internal tools, or high-performance systems.

Proven track record of delivering complex projects end-to-end in a high-ownership, fast-paced setting.

Ability to work cross-functionally and communicate effectively with non-engineering collaborators.

Nice-to-Have:

Experience in scientific tooling, data visualization, or engineering for R&D/ML workflows.

Familiarity with cloud infrastructure (GCP, AWS) and distributed computing environments.

Interest or background in biology, biotech, healthcare, or AI for science.