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alphasense
Страна
США
Зарплата
203 000 $ – 304 000 $
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Staff AI Platform Engineer

Оценка ИИ

Высокая заработная плата, работа с передовыми технологиями (LLM, AI-агенты) и статус компании как лидера рынка делают вакансию очень привлекательной. Позиция Staff уровня предполагает значительное влияние на продукт и архитектуру.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль уровня Staff требует не только глубоких технических знаний в области распределенных систем и Kubernetes, но и лидерских качеств для менторства команды и формирования технической стратегии всей платформы. Высокая планка ответственности за надежность (99.9%+) и работа с новейшими AI-агентами делают эту позицию крайне сложной.

Анализ зарплаты

Медиана255 000 $
Рынок210 000 $ – 320 000 $
Оценка ИИ

Предложенный диапазон $203k – $304k полностью соответствует рыночным стандартам для позиции Staff Engineer в Сан-Франциско, где медиана составляет около $250k-270k без учета опционов. Верхняя граница в $304k является очень конкурентоспособной даже для топовых технологических компаний.

Сопроводительное письмо

I am writing to express my strong interest in the Staff AI Platform Engineer position at AlphaSense. With over 8 years of experience in architecting distributed systems and a proven track record of scaling infrastructure to meet enterprise-grade reliability, I am excited by the opportunity to bridge the gap between cutting-edge AI research and robust production environments. My background in Kubernetes, microservices, and infrastructure-as-code aligns perfectly with your mission to transform how AlphaSense builds and operates AI-powered systems at scale.

In my previous roles, I have successfully led initiatives that improved system uptime from 99% to 99.99% while mentoring engineering teams on observability and CI/CD best practices. I am particularly impressed by AlphaSense's integration of LLMs and agentic systems to empower decision-making for the S&P 500. I am eager to bring my expertise in building resilient platforms to help your team productionize multi-model AI capabilities and ensure the platform remains performant as it continues its rapid growth.

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Откликнитесь в alphasense уже сейчас

Присоединяйтесь к AlphaSense, чтобы масштабировать передовые AI-системы и определять будущее интеллектуального поиска для крупнейших компаний мира.

Описание вакансии

About AlphaSense:

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.

The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role

AlphaSense is seeking an experienced engineering leader to transform how we build and operate AI-powered systems at scale. You'll join a team of brilliant engineers who've built cutting-edge AI applications, and your mission will be to bring world-class engineering practices that ensure these innovations run reliably for our enterprise customers.

This is a unique opportunity for a seasoned engineer who thrives on building robust platforms, mentoring talented teams, and establishing engineering excellence. You'll have significant autonomy to shape our technical architecture while working with frontier AI models and agentic systems that power market intelligence for the world's leading companies.

What You'll Do

  • Architect for Scale: Design and implement distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency
  • Build Engineering Excellence: Establish comprehensive testing strategies, observability systems, and CI/CD pipelines that catch issues before customers do
  • Lead Through Expertise: Mentor a team of smart, motivated engineers, sharing your experience in building production systems that don't break at 3 AM
  • Drive Platform Evolution: Own the technical roadmap for our AI platform, making architectural decisions that will shape our systems for years to come
  • Bridge AI and Engineering: Collaborate with ML engineers and researchers to productionize cutting-edge AI capabilities while maintaining system stability

What We're Looking For

Required:

  • 7+ years building and operating distributed systems in production
  • Track record of improving system reliability (taking services from frequent outages to 99.9%+ uptime)
  • Deep expertise in modern engineering practices: microservices, containerization (Kubernetes), infrastructure as code
  • Experience leading technical initiatives and mentoring engineering teams
  • Strong coding skills with ability to work across the stack
  • Excellence in debugging production issues and implementing comprehensive observability
  • History of making pragmatic trade-offs between perfect and shipped

Preferred:

  • Experience with LLM applications, agent frameworks, or AI/ML infrastructure
  • Familiarity with prompt engineering, RAG patterns, vector databases
  • Background at high-growth companies or modern engineering cultures
  • Experience with multi-model AI systems (OpenAI, Anthropic, Google, etc.)

Impact You'll Have

Within your first year, you'll transform how we build and operate software. You'll reduce incidents, establish testing and observability standards that become part of our DNA, and build platforms that enable other engineers to ship faster and safer. Most importantly, you'll elevate an entire team of engineers, sharing the expertise that only comes from years of building systems at scale.

For base compensation, we set standard ranges for all roles based on function and level benchmarked against similar stage growth companies and internal comparables. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors including candidate experience/expertise and may vary from the amounts listed below.

You may also be offered equity, and a generous benefits program.

Compensation Range

$203,000—$304,000 USD

AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.

In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.

Recruiting Scams and Fraud

We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:

  • AlphaSense never asks candidates to pay for job applications, equipment, or training.
  • All official communications will come from an @alpha-sense.com email address.
  • If you’re unsure about a job posting or recruiter, verify it on our Careers page.

If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.

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Навыки

  • Kubernetes
  • Distributed Systems
  • Microservices
  • Infrastructure as Code
  • CI/CD
  • Observability
  • LLM
  • RAG
  • Vector Databases
  • Python
  • Go

Возможные вопросы на собеседовании

Проверка опыта обеспечения высокой доступности в критически важных системах.

Расскажите о случае, когда вы перевели сервис с частыми сбоями на уровень доступности 99.9%+. Какие конкретные архитектурные изменения вы внедрили?

Оценка способности кандидата внедрять AI-модели в промышленную эксплуатацию.

Какие основные вызовы вы видите при масштабировании систем на базе LLM-агентов, и как бы вы организовали мониторинг их производительности и стоимости?

Проверка навыков системного дизайна и работы с инфраструктурой.

Как бы вы спроектировали CI/CD пайплайн для AI-платформы, чтобы минимизировать риск деградации моделей при обновлении инфраструктуры?

Оценка лидерских качеств и умения работать с командой.

Опишите ваш подход к менторству сильных инженеров. Как вы балансируете между установлением стандартов качества и предоставлением автономии команде?

Проверка умения принимать прагматичные решения.

Приведите пример, когда вам пришлось выбирать между 'идеальным' архитектурным решением и необходимостью быстрого запуска продукта. Чем вы руководствовались?

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alphasense
Страна
США
Зарплата
203 000 $ – 304 000 $