AI Hiring Index

Anthropic · Engineering · Staff+ · Posted 2026-07-22

Staff+ Software Engineer, Enterprise AI Products

Anthropic · San Francisco, CA | New York City, NY · $405k–485k base

This is one of the highest posted engineering ranges at AI companies right now. See the salary index.

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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 Enterprise AI Products team builds what makes Claude a daily-use tool for enterprise customers across industries. We focus on organizational context and workflows (plugins, skills, connectors, webhook-triggered processes / agents). In other words, we focus on products that form the connective tissue that lets Claude operate across an organization. A big part of this work is understanding what's blocking adoption and building the capabilities that close those gaps. Much of this is being built 0→1 right now: you'll be shaping the product and the architecture in a market where no one has done this well yet.

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.

What you'll do

Own technical design and delivery for enterprise-facing core products, end-to-end across the stack

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

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

Mentor other engineers and raise the technical bar across the team, working with influence rather than authority

Build multi-player, asynchronous agents: department-level processes that are goal-oriented, many-step, and triggered by a webhook, a form, or an email rather than a person typing

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

Experience building extensibility surfaces (plugins, integrations, agent tooling) that third parties or internal teams build on

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: Currently, we expect all staff to be in one of our offices at …

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