Original Title: I looked at 1,680 Anthropic resumes. Here's who they actually hire.
Original Author: @hiiinternet
Translated by: Peggy

Editor's note: The outside world often imagines Anthropic as an AI laboratory composed of PhDs, researchers, and cutting-edge model experts, but this breakdown of 1,680 engineer resumes provides a more realistic answer: Anthropic's core is not just "research," but "building."

This article analyzes 5,306 LinkedIn profiles listing Anthropic as current employer, then further filters out 1,680 engineer resumes, examining 7,986 past job descriptions to see what they were doing before joining Anthropic.

Here are the results.

Almost overnight, the organization expanded rapidly

Before 2021, only 15 engineers had joined Anthropic and are still employed there. By 2025, the engineering team had nearly tripled, adding 686 engineers that year; the hiring pace in 2026 is expected to be similar, with 455 new hires by June.

Currently, over half of the engineering team has been at Anthropic for less than a year. 53% joined within the past 12 months. Median tenure: 10 months.

This is a large organization, but it was built in just about 18 months.

Almost only hiring senior engineers

The median prior work experience of those joining Anthropic is 12.2 years. The middle 50% have between 8.8 and 16.5 years of experience. Among these 1,680 people, only 50 have less than 3 years of experience. 44% have 13 or more years of work experience. Hiring fresh graduates is basically nonexistent.

In other words, the typical new employee at Anthropic is an engineer with 12 years of experience, but only 10 months at Anthropic.

Clearly more focused on infrastructure than traditional research

Infrastructure background appears in 40% of engineer resumes. Backend, distributed systems, databases, and security each account for about 20%. Reinforcement learning, specifically RLHF, appears in only 3.3% of resumes.

The typical Anthropic engineer has spent the past decade building large-scale production systems at a hyperscale cloud provider or a startup focused on infrastructure.

Their listed skills also tell the same story: Python 585 people, Java 566, C++ 443, JavaScript 376, SQL 302, Linux 230, distributed systems 189, AWS 154. More "glamorous" model training work exists but makes up a small proportion.

The largest talent sources are not labs, but Google

Many assume Anthropic mainly recruits from OpenAI and DeepMind. But its biggest talent pipeline, far ahead, is Google. The competing labs are just small columns in the chart.

Anthropic clearly prefers those from companies known for engineering rigor: Stripe, Databricks, Snowflake, Palantir, Airbnb.

Looking at their employment history, the top sources are: Google 405, Meta 273, Amazon 197, Microsoft 171, Stripe 124, Apple 87, Stanford 68, DeepMind 62, Airbnb 51, OpenAI 48. Half of the current engineering team has at least one FAANG experience.

Of course, they also recruit from other AI labs. OpenAI is one of the top five direct sources, DeepMind one of the top six. About 94 engineers have directly jumped from other frontier AI labs to Anthropic.

Debunking the PhD myth

Only 13.7% hold a PhD. About one in seven.

Anthropic’s typical hiring target isn’t research scientists, but senior engineers with bachelor’s or master’s degrees. The image of "an entire lab full of PhDs" is basically wrong at the engineering team level.

The distribution of backgrounds also fits the profile of a "building-oriented organization": 819 in computer science, followed by 78 in mathematics, 70 in physics, 69 in computer engineering. Philosophy also ranks in the top 20 with 13 people, possibly related to safety focus.

Stanford leads in recruiting sources

From schools, the historical rankings are: Stanford 144, Berkeley 118, MIT 80, CMU 73, Harvard 42, Cambridge 39, UW 36, Waterloo and Cornell each 35, Oxford 33, Princeton 32. The top four schools together account for a quarter of the entire engineering team.

80% of the team share the same job title.

"Member of Technical Staff" (MoTS).

A former Instagram CTO, several former Adept founders, and Stanford faculty all hold only the "MoTS" title at Anthropic. This flat hierarchy is clearly intentional. Seniority and specific roles are hidden in the design.

Where is the only pathway for early-career talent to enter Anthropic?

172 engineers have less than 6 years of experience, with 50 under 3 years. But they are not typical fresh graduates. They roughly fall into two categories, with almost no mid-level engineers in between.

Compared to the whole team, they show distinct features: higher PhD proportion at 19% (vs. 13.7%), product/SWE titles three times more common at 15% (vs. 5%), and a much lower probability of FAANG experience at 32% (vs. 50%).

They substitute work experience with another form of prestige capital:

Internship pipelines. 50% of them list internships at companies like Meta (16), Google (10), DeepMind (6), Microsoft (5), Amazon (5), plus Jane Street, Two Sigma, HRT, Optiver, Nvidia.

From quantitative trading to AI labs. 9% have worked at top trading firms like Jane Street, Two Sigma, Five Rings, HRT, Optiver, Citadel. These are young, math/computer competition talents entering AI labs via high-frequency trading.

Alignment-focused fellowships. 6% have participated in MATS, SERI, Redwood, or ARC. These are almost exclusively early-career entry points, rarely seen among senior groups.

A very clear profile emerges: MIT, IOI silver medal, Codeforces 2900+ points, entering reinforcement learning and safety after four years. Their selection criteria are not work experience but competition rankings and publications.

These young engineers are also more international than senior engineers. Their educational backgrounds include: Berkeley 15, Stanford 14, Cambridge 10, MIT 7, Tsinghua 7, Oxford 6, plus Imperial, NUS, Shanghai Jiao Tong, ETH Zürich.

So, how should you interpret this information?

If you want to join Anthropic as an engineer, don’t write your resume as if applying to a research lab. Instead, showcase the large-scale systems you’ve built, expanded, and maintained. That’s what gets you hired.

Early career is the only exception. At this stage, the threshold isn’t just work experience but top internships, competition rankings, or publications.

If you’re competing with Anthropic for talent, your target isn’t "PhDs" or "lab backgrounds" per se, but experienced builders from hyperscale cloud providers or highly reputable engineering companies: roughly 12 years of experience, possibly from Stripe, Databricks, Snowflake, Palantir. Anthropic is already heavily recruiting from this pool.

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