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Applied AI Engineer (Startups)

Anthropic

Applied AI Engineer (Startups)

Anthropic

London, UK

·

On-site

·

Full-time

·

2w ago

Compensation

£225,000 - £240,000

Benefits & Perks

Equity

Unlimited PTO

Parental Leave

Flexible Hours

Equity

Unlimited Pto

Parental Leave

Flexible Hours

Required Skills

Python

LLM application development

Prompting

Agent architectures

Evaluation frameworks

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:
As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor helping the top AI-native startups build on the Claude Developer Platform as they grow from early product to scale. You'll lead deep technical engagements, partnering directly with startup engineering teams to help them develop their products on top of Claude—advising on implementation, agent design, and working alongside them to build at the frontier of AI.

Working closely with Applied AI Architects, Account Executives, and Anthropic's Product and Engineering teams, you'll guide startups through deep technical engagements. You'll leverage your AI engineering expertise to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable startups to succeed with Claude.

Responsibilities:

Serve as a deep technical advisor to high-potential startups, working alongside them to build innovative use cases that push the boundaries of AI

Work hands-on with startup engineering teams: pair programming, architecture reviews, and code contributions that accelerate their development

Develop prototypes and technical documentation—including evaluation suites, AI engineering techniques, and architecture diagrams—that enable startups to build and scale with Claude

Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements

Identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team

Create technical content for startup audiences including documentation, tutorials, and sample code

Foster community engagement through hackathons, webinars, technical office hours, and startup-focused events

Travel to customer sites for workshops, implementation support, and relationship building

You may be a good fit if you have:
4+ years of experience as a Software Engineer, Forward Deployed Engineer, or technical founder

Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale

Strong programming skills with proficiency in Python and experience building production applications

Experience with startups or high-growth companies

Ability to context-switch across industries (healthcare, fintech, etc.) and use cases

Builder credibility that earns trust with technical founders and engineering teams—you've shipped products and can speak from experience

Strong technical communication skills with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans

Experience facilitating technical workshops, hackathons, or developer-focused events

Passion for making powerful technology safe and beneficial

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:£225,000—£240,000 GBP

Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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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About Anthropic

Anthropic

Anthropic

Series F

An AI safety and research company that builds reliable, interpretable, and steerable AI systems.

1,001-5,000

Employees

San Francisco

Headquarters

$60B

Valuation

Reviews

4.5

20 reviews

Work Life Balance

3.0

Compensation

4.5

Culture

4.8

Career

4.2

Management

3.5

100%

Recommend to a Friend

Pros

Exceptional team quality and talent

Cutting-edge AI and technical work

Strong mission-driven culture

Cons

Long working hours

Opaque leadership and management

High learning curve and fast pace

Salary Ranges

31 data points

Junior/L3

Senior/L5

Junior/L3 · Data Scientist

4 reports

$212,318

total / year

Base

$163,322

Stock

-

Bonus

-

$181,358

$213,724

Interview Experience

5 interviews

Difficulty

4.0

/ 5

Offer Rate

40%

Experience

Positive 40%

Neutral 40%

Negative 20%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Technical Interview

5

System Design Round

6

Final Round/Onsite

7

Offer

Common Questions

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR

ML/AI Concepts