Staff+ Software Engineer (Claude Science)

Join Anthropic, a company dedicated to creating reliable, interpretable, and steerable AI systems. As a Staff+ Software Engineer for Claude Science, you will play a key role in building an AI workbench that accelerates scientific progress across various fields. You will have the opportunity to shape both the product and architecture, interface directly with working scientists, and partner with product and design teams.

• Concevoir et développer des systèmes d'IA fiables, interprétables et pilotables pour accélérer le progrès scientifique.
• Travailler en étroite collaboration avec des scientifiques et des équipes de recherche pour comprendre leurs besoins et traduire ces informations en priorités d'ingénierie.
• Diriger des initiatives techniques, établir des orientations techniques et assurer l'alignement entre les équipes pour livrer un travail impactant.

• Are comfortable working directly with technical domain experts and translating what you learn
• Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on
• Have built AI products and know what it takes to turn model capabilities into applications people actually use
• Drive cross-team alignment to ship impactful work, with influence over authority
• Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work
• Background in chemistry, biology, physics, or another science
• Experience working with research teams to improve domain-specific model capabilities, including evaluation frameworks