ROLE OVERVIEWWe're a team building AI for scientists, including agents that automate toil in everyday scientific work and models that help scientists design better molecules. Our goal is to democratize access to AI, putting it in the hands of every scientist. As an engineer on the team, you'll build product experiences that drive adoption of AI across the hundreds of thousands of scientists who use Benchling today. You'll blend strong technical skills and deep product intuition, working across our stack to optimize onboarding, create viral loops, and help scientists understand how to leverage AI in their daily workflows. It's early days for scientific AI, both at Benchling and in the industry at large. We'll rapidly iterate with customers and change directions quickly, figuring out new patterns for how we develop and go to market. We'll win if we stay curious and obsess over our customers.
RESPONSIBILITIES- Build end-to-end product experiences that drive adoption of scientific AI, from onboarding flows to in-product discovery, education, and feedback loops.
- Work directly with customers to understand use cases, gather feedback, and onboard scientific teams.
- Experiment rapidly, designing and running A/B tests, instrumentation, and data analyses to identify the biggest levers for user activation and retention.
- Continuously improve our growth platform, developing frameworks and tooling that make it easier to test, measure, and scale successful experiments.
- Shape how we build AI at Benchling, evolving our engineering and product development practices to define what great AI adoption looks like in the scientific world.
QUALIFICATIONS- 5+ years of experience building delightful, consumer-grade products, ideally at a company where growth and experimentation were core to the strategy.
- Full-stack engineering skills, with experience in modern frontend frameworks (React or equivalent) and backend languages (Python or similar).
- Strong product and growth intuition, with the ability to iterate quickly and refine solutions based on user feedback and data.
- Experience with instrumentation and analytics, including defining success metrics, implementing event tracking, and using data to drive decisions.
- Desire to work in a fast-paced environment, forming hypotheses, testing ideas quickly, and scaling the ones that work.
- Interest in learning about biotechnology and AI (no prior knowledge required, just a willingness to learn and adapt).
HOW WE WORKThis is an in-person team in San Francisco built around collaborating in the office in a fast-paced environment. We're in the office Monday through Friday.
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