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anthropic
Страна
Япония
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Applied AI Engineer

Оценка ИИ

Работа в одной из самых влиятельных ИИ-компаний мира над передовыми технологиями. Высокий престиж, работа с топовыми клиентами и возможность влиять на развитие Claude делают эту вакансию исключительно привлекательной.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует редкого сочетания глубоких технических знаний в области LLM (промпт-инжиниринг, агенты, RAG) и отличных навыков работы с клиентами. Высокая планка Anthropic к безопасности и этике ИИ добавляет дополнительный уровень сложности при отборе.

Анализ зарплаты

Медиана160 000 $
Рынок130 000 $ – 220 000 $
Оценка ИИ

Зарплата для этой роли в Токио значительно выше среднего по рынку для обычных разработчиков, отражая дефицит специалистов по LLM и премиальный статус компании Anthropic. Указанный диапазон соответствует уровню Tier-1 технологических компаний в Японии.

Сопроводительное письмо

I am writing to express my strong interest in the Applied AI Engineer position at Anthropic in Tokyo. With over four years of experience in technical customer-facing roles and a deep focus on Large Language Models, I have closely followed Anthropic’s commitment to building reliable and steerable AI systems. My background in developing evaluation frameworks and implementing complex LLM patterns aligns perfectly with your mission to help customers deploy Claude safely and effectively.

In my previous roles, I have successfully bridged the gap between complex technical architectures and business objectives, a skill I am eager to bring to the Applied AI team. I am particularly excited about the opportunity to guide Japanese enterprises through the nuances of prompt engineering and agent development. My proficiency in Python, combined with a high-cooperation mindset, ensures that I can contribute to both customer success and the continuous improvement of Anthropic’s product suite.

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Откликнитесь в anthropic уже сейчас

Присоединяйтесь к Anthropic в Токио и помогайте ведущим компаниям внедрять Claude в их продукты!

Описание вакансии

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 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.

As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to customers as they adopt Claude. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting edge implementation patterns for LLMs.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

  • Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
  • Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation
  • Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API
  • Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API
  • Lead hands-on technical workshops and code reviews with customer engineering teams
  • Identify common design patterns and contribute insights back to our Product and Engineering teams
  • Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
  • Travel occasionally to customer sites for workshops, implementation support, and building relationships
  • Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

  • 4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers
  • Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale
  • Strong programming skills with proficiency in Python and experience building production applications
  • Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.
  • Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
  • High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
  • Passion for advancing safe, beneficial AI systems through creative technical applications
  • Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Deadline to apply:None. Applications will be reviewed on a rolling basis.

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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Навыки

  • Python
  • LLM
  • RAG
  • Prompt Engineering
  • Software Architecture
  • Generative AI
  • Technical Consulting
  • AI Agents

Возможные вопросы на собеседовании

Проверка практического опыта работы с моделями Anthropic и понимания их особенностей.

Можете ли вы описать случай, когда вам пришлось оптимизировать промпты для Claude, чтобы избежать галлюцинаций или улучшить следование сложным инструкциям?

Оценка навыков архитектурного проектирования для клиентов.

Как бы вы спроектировали систему оценки (evaluation framework) для клиента, который хочет внедрить ИИ-агента в свой цикл обслуживания клиентов?

Проверка умения работать в условиях неопределенности и решать конфликты интересов.

Как вы расставляете приоритеты, когда требования клиента по скорости внедрения вступают в конфликт с внутренними стандартами безопасности Anthropic?

Оценка технической глубины в области современных паттернов ИИ.

В чем, по вашему мнению, заключаются основные сложности при масштабировании RAG-систем для крупных корпоративных баз данных?

Проверка коммуникативных навыков и умения объяснять сложные вещи просто.

Как бы вы объяснили концепцию 'конституционального ИИ' техническому директору компании, который далек от исследований в области безопасности?

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anthropic
Страна
Япония