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.
Anthropic's Verticals team builds AI products purpose-built for specific industries — financial services, science, healthcare, and the broader enterprise. Most of these teams are being built 0→1 right now: you'll be shaping the product and the architecture in markets where no one has done this well yet. Where we're further along, products are already live with enterprise customers and growing fast.
We're hiring Staff+ Software Engineers to build the products that bring Claude into financial services, science, healthcare, and enterprise AI workflows. You'll be a technical leader who thinks holistically about the end-to-end customer experience, partners directly with research to push model capabilities into production, and carries real ownership over what we ship next.
We're hiring across all of these areas through this posting. Team placement happens during the interview process based on your background, interests, and organizational need — if you have deep experience in one of these domains, let us know in your application.
Claude for Financial Services — Builds products for customers in investment banking, asset management, insurance, and corporate finance. Near-term work centers on deeply integrated experiences inside the tools these teams already use, with a roadmap expanding as we learn what's most useful. The team operates close to enterprise customers and close to research.
Claude Science — We just launched Claude Science, an AI workbench for scientists that brings fragmented research tools into a single environment. The product is live and expanding fast; you'll help drive engineering through that growth.
Claude for Healthcare — The focus is payer workflows (claims, prior authorization, utilization management, member communications), with groundwork for clinical applications over time. You'll be shaping the product and the architecture at the same time.
Enterprise AI Products — Building what makes Claude a daily-use tool for enterprise customers across industries: plugins, skills, and shared organizational context — the connective tissue that lets Claude operate across an organization's workflows — plus the foundational systems large organizations require to deploy AI at scale, like user and permissions management, security and compliance features, and analytics infrastructure. A big part of this work is understanding what's blocking adoption and building the capabilities that close those gaps.
Own technical design and delivery for a core piece of one of these vertical or enterprise products, end-to-end across the stack
Work closely with research to make the models better in your domain — shaping evals, surfacing failure modes, and feeding customer learnings back into model development
Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec
Set technical direction and standards for your team — architecture, code quality, and how the team builds
Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities
Mentor other engineers and raise the technical bar across the team, working with influence rather than authority
Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level
Have led the design and delivery of complex enterprise or B2B products across the full stack
Have built AI products and know what it takes to turn model capabilities into applications people actually use
Are comfortable working directly with enterprise customers and translating what you learn into technical decisions
Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on
Drive cross-team alignment to ship impactful work, with influence over authority
Experience working with research to improve domain-specific model capabilities, including evaluation frameworks
Deep domain knowledge in one of these areas: investment banking, asset management, insurance, or corporate finance; scientific research or computational biology; clinical operations, health systems, or payers; or enterprise platform work
Exposure to both product-led growth and direct enterprise sales
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 USDMinimum 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.
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.
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.
