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alphasense
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Индия
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Ускорим процесс поиска работы
SeniorУдалённоПолная занятость

Senior Software Engineer - Search

Оценка ИИ

Отличная вакансия в стабильной компании-единороге с интересным технологическим стеком (Vespa, Kubernetes, Hybrid Search) и удаленным форматом работы. Высокий уровень ответственности и влияние на продукт.


Вакансия из Quick Offer Global, списка международных компаний
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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена требованиями к глубоким знаниям распределенных систем, опытом работы с миллиардами документов и необходимостью проведения миграции архитектуры без простоев.

Анализ зарплаты

Медиана65 000 $
Рынок5 000 $ – 85 000 $
Оценка ИИ

Предлагаемая роль Senior-уровня в международной компании уровня AlphaSense в Индии обычно предполагает компенсацию выше среднего по рынку, учитывая сложность задач и удаленный формат.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Software Engineer - Search position at AlphaSense. With over 6 years of experience in building and scaling high-throughput distributed systems, I have developed a deep expertise in sharding, replication, and performance optimization. My background in architecting robust data platforms aligns perfectly with your mission to deliver reliable market intelligence across billions of documents.

In my previous roles, I have successfully led migrations from legacy architectures to modern, Kubernetes-based systems while maintaining zero downtime. I am particularly drawn to this role because of the opportunity to work with hybrid lexical and vector search technologies. I am confident that my focus on engineering excellence, observability, and system reliability will help AlphaSense continue to provide the world-class insights its enterprise customers depend on.

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Составьте идеальное письмо к вакансии с ИИ-агентом

Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в alphasense уже сейчас

Присоединяйтесь к AlphaSense и создавайте поисковые системы нового поколения на базе ИИ!

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 Role

AlphaSense is seeking an experienced engineer to work on the search platform that powers market intelligence across billions of documents. You'll tackle the challenge of building distributed systems that handle hundreds of queries per second with millisecond latency, while establishing engineering excellence that ensures reliability for our enterprise customers.

This role is perfect for a seasoned engineer who loves challenges and has a track record of building robust, high-performance systems. While search experience is valuable, we believe great engineers can master new domains – what matters most is your ability to build systems that scale and don't break.

What You'll Do

  • Scale Distributed Systems: Architect and optimize infrastructure handling billions of documents and hundreds of queries per second
  • Lead Platform Evolution: Drive the migration from legacy systems to modern architecture, ensuring zero downtime and improved performance
  • Build Engineering Excellence: Establish comprehensive monitoring, testing, and deployment practices that catch issues before customers do
  • Optimize Performance: Profile and tune systems from the infrastructure to the application level, balancing cost and performance

What We're Looking For

Required:

  • 5+ years building and operating distributed systems in production
  • Experience with large-scale data platforms or high-throughput systems
  • Expertise in distributed systems fundamentals: sharding, replication, consistency, partition tolerance
  • Strong performance optimization skills - you can profile, diagnose, and fix bottlenecks across the stack
  • Experience with data pipeline architecture, real-time processing, or database internals
  • Excellence in building observable systems with comprehensive monitoring and alerting

Preferred:

  • Experience with search platforms (Vespa, Elasticsearch, Solr) or similar large-scale data systems
  • Experience with Kubernetes, CRDs, and infrastructure as code
  • Background in information retrieval, ranking systems, or recommendation engines
  • Familiarity with hybrid search approaches (lexical and vector)
  • Experience with JVM-based systems and tuning
  • Knowledge of modern engineering practices from high-growth companies

Why This Role is Unique

You'll own a critical platform that directly impacts how customers discover insights. This isn't just about maintaining a search system – it's about building the next generation of information retrieval at scale. You'll work with modern technologies (including hybrid lexical/vector search), but more importantly, you'll apply your distributed systems expertise to solve fascinating scale challenges.

The best part? You'll join a team of smart engineers who are eager to learn. Your experience in building bulletproof systems will directly elevate the entire team's capabilities.

Impact You'll Have

Within your first year, you'll transform our search infrastructure from reactive to proactive, reduce latency, complete a major platform migration, and build systems that scale effortlessly with our growth. Most importantly, you'll establish engineering practices that ensure we never hear about customer issues first.

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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Создайте идеальное резюме с помощью ИИ-агента

Создайте идеальное резюме с помощью ИИ-агента

Навыки

  • Distributed Systems
  • Kubernetes
  • Java
  • Vespa
  • ElasticSearch
  • Solr
  • Infrastructure as Code
  • Information Retrieval
  • Vector Search
  • Monitoring
  • Performance Optimization

Возможные вопросы на собеседовании

Проверка фундаментальных знаний распределенных систем, критически важных для масштабирования поиска.

Как бы вы спроектировали систему шардирования для индекса из миллиардов документов, чтобы минимизировать задержки при поиске?

Вакансия предполагает миграцию с legacy-систем. Важно понять опыт кандидата в обеспечении стабильности.

Расскажите о вашем опыте миграции крупной системы в продакшене: как вы обеспечивали нулевое время простоя и проверяли целостность данных?

Поиск в AlphaSense требует высокой производительности. Вопрос проверяет навыки профилирования.

Опишите случай, когда вы обнаружили узкое место в производительности распределенной системы. Какие инструменты и методы вы использовали для диагностики?

В описании упоминается важность мониторинга. Проверка подхода к надежности.

Какие ключевые метрики (SLI/SLO) вы бы внедрили для поисковой платформы, чтобы проактивно выявлять проблемы до того, как их заметит клиент?

Вакансия упоминает гибридный поиск. Проверка знакомства с современными трендами IR.

В чем заключаются основные сложности при совмещении традиционного лексического поиска и векторного (semantic) поиска в одной системе?

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alphasense
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