About Scispot
The Best Data Infrastructure for Biotechs. Backed by Y Combinator.
About the role
We are looking for a senior backend and infrastructure engineer who treats production as a product. You will own the systems beneath Scispot: backend services, messaging, databases, cloud infrastructure, CI/CD, observability, security, and reliability.
What they're looking for
- Roughly 3+ years of experience building and operating backend, platform, DevOps, SRE, or infrastructure systems. Strong evidence matters more than a precise year count
- Strong production backend experience with Python and FastAPI, Java and Spring Boot, or a comparable stack
- A solid grasp of distributed systems, asynchronous processing, failure modes, retries, idempotency, and message-driven architecture
- Hands-on experience with AWS and Azure. You have made practical decisions about networking, compute, storage, identity, security, and cost
- Solid understanding of AI pipelines, prompt looping, langfuse tracing, and context engineering
- Experience with Docker and Kubernetes. Production EKS experience is especially useful
More about this role
This is a hands-on backend and infrastructure role. You will write production code, make architecture choices, and own systems from design through deployment, monitoring, and incident response.
- Scispot began after my brother Guru and I (Satya) watched someone they loved run out of time while slow, manual lab processes delayed a promising treatment. We are building Scispot so life-saving science can move at software speed.
- Biotech & Lifescience teams should not have to choose between moving fast and keeping their data clean, connected, traceable, and ready for AI.
- We are building the digital backbone for scientific discovery. Scispot connects lab operations, instrument data, scientific workflows, and AI-driven insights in one platform. This becomes the memory layer for lifescience teams for their agents.
- Your code will not optimize clicks for another consumer app. It will help scientists run experiments faster, trace samples accurately, automate repetitive work, and move treatments closer to patients.
- This is a rare chance to build infrastructure at the intersection of software, AI, data, and biology.
Today, Scispot supports more than 100 labs, 250+ instrument types, over...
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