Software Engineer (Agents)
- San Francisco, United States
- Mid Level
- 3+ years
- Posted
Skills
Required
- software engineering
- ideas
- backend systems
- Python
- modern frontend frameworks
- React
Join Benchling, a leading platform for life sciences R&D. As a Software Engineer on our AI agents team, you'll build end-to-end AI agents that automate scientific work, from experiment design to data analysis and reporting. You'll work directly with customers, engineer across the stack, and continuously improve our agent platform. This is an exciting opportunity to shape the future of AI in scientific research.
USD 194,369 - 265,388
Responsibilities
- Construire des agents d'IA de bout en bout, en prototypant et en mettant en production des systèmes qui automatisent le travail scientifique, de la conception d'expériences à l'analyse des données et à la rédaction de rapports.
- Travailler directement avec les clients pour imaginer des cas d'utilisation, recueillir des commentaires, construire des évaluations et intégrer des équipes scientifiques.
- Contribuer à l'amélioration continue de notre plateforme d'agents, en contribuant aux frameworks, aux outils et à l'infrastructure qui accélèrent le développement futur des agents.
Requirements
- 3+ years of professional software engineering experience, building and maintaining production systems
- Interest in learning about biotechnology (no prior knowledge required, just a willingness to learn and adapt)
- Collaborative mindset, able to work closely with engineers, product managers, and scientists to bring new ideas to life
- Desire to work in a fast-paced environment, where priorities can shift and rapid experimentation is encouraged
- Curiosity and excitement about LLMs and AI agents, and a desire to shape how they can transform scientific research
- Experience across the stack, comfort working with backend systems (Python or similar languages) and modern frontend frameworks (React or equivalent)
- Strong product sense, with the ability to iterate quickly and refine solutions based on user feedback and data
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