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Staff+ Software Engineer, Enterprise Knowledge Work

Job in New York City, Richmond County, New York, USA
Listing for: Anthropic
Full Time position
Listed on 2026-08-09
Job specializations:
  • Software Development
    Backend Developer, AI Engineer (Applied/Software), Software Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 405000 - 485000 USD Yearly USD 405000.00 485000.00 YEAR
Job Description & How to Apply Below

Staff+ Software Engineer, Enterprise Knowledge Work

San Francisco, CA | New York City, NY

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 Knowledge Work team builds the products that help enterprise knowledge workers collaborate deeply with Claude for major parts of their work.

Over the past year, AI has transformed how software engineering happens; for the rest of knowledge work, though, using AI still mostly means answering questions and producing first drafts — a small slice of the actual job.

We're building toward something bigger: people and agents working together on every core work objective, from first idea to finished product, and the recurring work of a team running with Claude in the loop instead of a person pushing every step. It's an enormous space, it's early, and no one has built it well yet.

You'll help decide what these products are, not just how they're built — the product questions are as open as the architecture ones — and you'll see your work land with real teams at the world's largest enterprises.

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 the core primitives that enable knowledge workers across industries and roles to meaningfully leverage Claude
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 customer-facing 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 as startup founders or early-stage employees
Logistics

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

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…

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