EngineeringNot provided by source

Staff+ Software Engineer, Enterprise AI Products

Anthropic · Not provided by source

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Last seen by MeritLog September 12, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

MeritLog read this listing from Anthropic's Greenhouse job board and last checked it on September 12, 2026.

Source: the employer's Greenhouse job board. Open the original listing for current details.

Job details

Work model: Not provided by source
Salary: $405,000 – $485,000 per year
Location: San Francisco, CA | New York City, NY

Hiring context

How this role compares at Anthropic

Anthropic has 596 live roles in MeritLog’s catalog across 13 job families, and 181 of them are in engineering. 499 of those listings publish a pay range, a disclosure rate of 84%.

This role's posted range of $405,000 – $485,000 per year sits above 80% of the 456 other Anthropic roles quoted over the same currency and period.

Anthropic concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd 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

What they're asking for

Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership levelExperiencePreferred
Have led the design and delivery of complex enterprise or B2B products across the full stackSkill
Have built AI products and know what it takes to turn model capabilities into applications people actually useSkill
Are comfortable working directly with enterprise customers and translating what you learn into technical decisionsSkill
Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean onSkill
Drive cross-team alignment to ship impactful work, with influence over authoritySkill
Experience working with research to improve domain-specific model capabilities, including evaluation frameworksSkill
Experience building extensibility surfaces (plugins, integrations, agent tooling) that third parties or internal teams build onSkill
Exposure to both product-led growth and direct enterprise salesSkill

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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 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 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.

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