Staff+ Software Engineer, Vertical AI Products (Multiple Roles)

About the role

Anthropic's Verticals team builds AI products purpose-built for specific industries, including financial services, science, healthcare, and the broader enterprise. Most of these teams are being built 0→1 right now, with you shaping the product and the architecture in markets where no one has done this well yet. You'll be a technical leader who thinks holistically about the end-to-end customer experience, works closely with research to push model capabilities into production, and carries real ownership over what we ship next.

Responsibilities

• Own technical design and delivery for a core piece of one of these verticals 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
• Drive cross-team alignment to ship impactful work, with influence over authority

Requirements

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: 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level

Qualifications

• 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
• Strong candidates may also have 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

Skills

• 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

Benefits

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

Pay

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.

Schedule

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.

Guidance on Candidates' AI Usage

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.