Staff+ Software Engineer, Vertical AI Products (Multiple Roles)
About the role
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.
About the teams
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.
What you'll do
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
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 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
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 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
We currently 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.
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.
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