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Software Engineer, Search NY

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Anthropic Limited
Full Time position
Listed on 2026-10-17
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 320000 - 405000 USD Yearly USD 320000.00 405000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer, Search  | New York City, NY

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

We're building Anthropic's search platform team to create scalable, efficient search capabilities that power Claude's ability to access and retrieve information. In this role, you'll design and implement core search systems from the ground up.

Responsibilities:

Work with a small, senior team of engineers and researchers to build Anthropic’s search platform from scratch

Establish metrics and tooling to measure and improve search quality

Enhance search algorithms and indexing mechanisms to boost search accuracy and efficiency

You may be a good fit if you:

5+ years building complex distributed systems in production

Solid grasp of search fundamentals: indexing, retrieval, ranking

Strong coding skills in Python, Go, Java, or similar languages

Hands-on experience with high-volume data processing architectures

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.

$320,000 - $405,000 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 fromemail 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  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…

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