Staff Software Engineer
Job description
About the role
You are the person who sets the architectural direction for Kernel, translating high level ambitions into concrete, evolvable structures that outlast any single project. You own the long term evolution of the platform by making and justifying critical decisions about data models, API contracts, and system behavior. You act as a direct interface with synthetic biologists and computational biologists, listening to their workflows and turning nuanced biological questions into precise software requirements. You clarify priorities by understanding how experimentalists actually work, ensuring the tools you build remove friction rather than add to it. You take responsibility for software continuity, mentoring other engineers, and ensuring that the systems you create remain reliable and maintainable over many years. You write clear, reasoned arguments for your technical choices and communicate complex tradeoffs in plain language so that the entire interdisciplinary team can participate in the discussion. You balance deep implementation work with strategic thinking, ensuring that today's code and today's decisions do not become tomorrow's crippling technical debt.
Key facts
What you'll do
Design and evolve GraphQL APIs in Python 3 that allow genetic constructs to be searched, edited, and analyzed with precision and performance.
Architect data models that capture biological system complexity while remaining flexible enough to support changing experimental requirements over many years.
Collaborate closely with synthetic biologists to identify and streamline their productivity tools by observing and questioning their daily workflows.
Work alongside computational biologists to ensure that the abstractions in the platform reflect the realities of biological data and analysis.
Participate in on-call rotations for the software you build, taking responsibility for reliability, incident response, and steady improvements to operational robustness.
Make system level decisions that balance complex API design, safe data migrations, and scalability to support tenfold increases in usage without painful rewrites.
Navigate poorly defined problems by framing questions, clarifying constraints, and collaborating with a small, cross functional team to design coherent products without predefined specifications.
Write tests, fix bugs, and refactor legacy code so that the platform remains maintainable as it grows in scope and usage.
Champion code reviews and knowledge sharing so that the team can sustain high quality standards and reduce bus factor across critical services.
Translate ambiguous biological needs into concrete software epics, milestones, and deliverables that the engineering team can execute against with confidence.
Requirements
You hold a bachelor's degree or higher, as stated in the official listing, and you have built production software that other engineers depend on across a timeline of 10+ years.
You have deep expertise in Python 3 and are comfortable with GraphQL, SQLAlchemy, and Strawberry, using these tools to build reliable, well tested APIs.
You reason about complex systems, designing APIs, planning data migrations, and thinking through scalability implications when usage grows 10x.
You are comfortable navigating significant ambiguity while working closely with a small, interdisciplinary team to arrive at a product vision that was not handed to you in a spec.
You have a track record of turning research grade code into robust, production grade systems that can be maintained and extended long after the initial prototype.
You communicate clearly in both written and spoken form, and you can explain technical tradeoffs in plain words to non specialists and experts alike.
You are expected to contribute to planning discussions, code reviews, and debugging sessions, not only writing new features but also sustaining the health of the codebase.
You hold the discipline and curiosity required to learn new domains, such as synthetic biology, well enough to collaborate effectively with domain experts.
Nice to have
Experience working at the intersection of software engineering and scientific domains, where abstractions must align with wet lab realities.
Familiarity with workflow systems, experiment tracking, or data pipelines common in computational biology or biotechnology.
Understanding of how experimental feedback loops can inform software evolution in fast moving research environments.
Practical notes
The role is based in Boston, MA, and the position is full_time.
This role requires a degree as stated in the listing.
Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
The tools used include Python 3, GraphQL, SQLAlchemy, and Strawberry for data and API work.
The culture values recombination, drawing on diverse backgrounds and perspectives to solve hard problems.
Work spans cells, software, and experimental feedback in a single integrated platform.
Questions to ask
Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.
About the company
Isaac Asimov was an American writer and professor of biochemistry at Boston University. During his lifetime, Asimov was considered one of the "Big Three" science fiction writers, along with Robert A.