Software Engineer, Internal Platforms

Description du poste

We're a biotech startup, and our software isn't a side product — it runs the business. Quoting, inventory, manufacturing execution, operational workflows, internal decision-making: all of it is custom software we build and operate ourselves. The stack is primarily Python on Google Cloud.
Most software jobs move a metric on a dashboard. Here, your work determines how products get manufactured, how orders get processed, how inventory is tracked, and how our lab and manufacturing teams spend their day.

You will own the day-to-day health of business-critical systems, and you'll expand them as you go.
Concretely: things break, and you fix them. Someone in operations needs a small feature, and you ship it. A data pipeline silently stops, and you notice before anyone else does. A spreadsheet has outgrown itself, and you turn it into a real system.
This is not a narrowly scoped frontend, backend, DevOps, or data engineering job. You'll work across application code, cloud infrastructure, data pipelines, integrations, and operational tooling.
It is also not an architecture role — the architecture exists, and your job is to keep it running well and extend it sensibly. You'll design within the system, not the system itself: when the lab needs to start capturing new metadata, you know that belongs in the schema as a first-class entity, not hard-coded or stuffed into a JSON field. That kind of judgment is the job.
You'll join our Chief Architect as the second engineer building and operating the software platform.

Profil recherché

A BS or higher in computer science, computer engineering, or a closely related field. We care about formal grounding — data structures, systems, algorithms, how a computer actually works. This is a firm requirement.
3+ years of professional software engineering experience
Strong Python
Solid SQL and real relational modeling instincts — you understand cardinality, you extend schemas rather than working around them, and you can tell when a shortcut today becomes a migration nobody wants to run
Comfortable with TDD, or eager to work that way
Experience deploying and operating cloud services in production
Ability to read an unfamiliar codebase and orient yourself without hand-holding
Ability to independently diagnose and resolve production issues
Clear communication with people who don't write software
And one of the following: experience or background in biotech, molecular biology, or laboratory science — enough that manufacturing workflows will be interesting to you rather than opaque; or genuine interest in biotech, plus a demonstrated track record of gathering and defining requirements in an interdisciplinary environment, where the people you were building for spoke a different professional language than you did.
You think like an engineer: you form a hypothesis, you check it, you find the actual root cause instead of the plausible one. You prefer the boring solution that works. You are suspicious of complexity you can't justify — and you notice when a physical process could be defined sharply enough to be measured.
This is execution work, but not thoughtless execution. The difference between a data model that lasts and one that gets ripped out is whether the person building it understood the whole system. We want someone who thinks hard and then ships.
And you close tickets. The satisfaction of this job comes from systems that stay up, bugs that stay fixed, and colleagues who stop having to do a thing by hand.
Manufacturing, operations, biotech, or lab environments
Google Cloud Platform
Workflow automation and internal tooling
On-call or production support experience
Startups or small engineering teams
You independently support most production systems
You diagnose and resolve operational incidents on your own
You independently own and ship routine features
You understand the key manufacturing and business workflows
People across the company come to you directly, because they know things get fixed or make their life easier