Job description

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we’re just getting started. Much of this is being built 0→1 right now: you’ll shape both the product and the architecture in a category no one has defined yet. You'll be a technical leader who thinks holistically about the end-to-end researcher experience, partners directly with our internal research team to push model capabilities into production, and carries real ownership over what we ship next. Our north star is accelerating scientific progress — across biology, chemistry, physics, and beyond — from early discovery through real-world application, by an order of magnitude. This work supports programs like Anthropic’s AI for Science Program and our rare disease research grants . What you'll do Ship fast against a roadmap you help shape: this is a product in a category no one has defined yet, and the highest-leverage problems are still unclaimed Interface directly with working scientists — academic labs, industry R&D teams, and research institutes — during key conversations, translating what you learn into engineering priorities Partner with product and design to turn how scientists actually work — from hypothesis to analysis to publication — into shipped product Work closely with research to make the models better at science: shaping evals, surfacing failure modes, and feeding what users hit in the real world back into model development You may be a good fit if you Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level 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 Are comfortable working directly with technical domain experts and translating what you learn Drive cross-team alignment to ship impactful work, with influence over authority Strong candidates may also have Background in chemistry, biology, physics, or another science Experience working with research teams to improve domain-specific model capabilities, including evaluation frameworks The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics 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 Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. 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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Requirements

Must-haves

Ship fast against a roadmap you help shape: this is a product in a category no one has defined yet, and the highest-leverage problems are still unclaimed
Interface directly with working scientists — academic labs, industry R&D teams, and research institutes — during key conversations, translating what you learn into engineering priorities
Partner with product and design to turn how scientists actually work — from hypothesis to analysis to publication — into shipped product
Work closely with research to make the models better at science: shaping evals, surfacing failure modes, and feeding what users hit in the real world back into model development
You may be a good fit if you
Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level
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
Are comfortable working directly with technical domain experts and translating what you learn
Drive cross-team alignment to ship impactful work, with influence over authority
Strong candidates may also have
Background in chemistry, biology, physics, or another science
Experience working with research teams to improve domain-specific model capabilities, including evaluation frameworks
The annual compensation range for this role is listed below.
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
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
How we're different
Come work with us!

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Parental Leave