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alphasense
Страна
Канада
Зарплата
202 000 CA$ – 278 000 CA$
+500% приглашений

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УдалённоПолная занятость

Principal Software Engineer

Оценка ИИ

Высокая оценка обусловлена престижем компании, работой с передовыми технологиями ИИ и очень конкурентоспособной заработной платой. Роль предлагает значительное влияние на продукт и архитектуру в глобальном масштабе.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует исключительного опыта (более 15 лет) и глубоких знаний в области распределенных систем и ИИ. Основная сложность заключается в необходимости объединения вероятностных моделей ИИ с детерминированными системами для обеспечения финансовой точности данных.

Анализ зарплаты

Медиана195 000 CA$
Рынок170 000 CA$ – 260 000 CA$
Оценка ИИ

Предлагаемая зарплата (202-278 тыс. CAD) находится на верхнем уровне рынка для позиции Principal Engineer в Канаде. Она значительно превышает медиану для Senior ролей, что соответствует высокому уровню ответственности и требуемому стажу в 15+ лет.

Сопроводительное письмо

I am writing to express my strong interest in the Principal Software Engineer position at AlphaSense. With over 15 years of experience in building large-scale distributed systems and a deep focus on data ingestion and processing, I am excited by the challenge of evolving your global financial data extraction platform. My background in combining deterministic systems with probabilistic AI models aligns perfectly with your mission to reduce human dependency while maintaining the highest standards of data integrity.

Throughout my career, I have specialized in architecting platforms that handle heterogeneous data sources and implementing robust observability and confidence-scoring mechanisms. I have a proven track record of leading technical strategy across multiple teams and mentoring senior engineers to raise the bar for system design. I am particularly drawn to AlphaSense’s commitment to using AI responsibly to deliver high-confidence insights to the world’s leading companies.

I am confident that my expertise in distributed systems and data platform engineering will allow me to make immediate contributions to your Product & Engineering team. I look forward to the possibility of discussing how my technical leadership can help AlphaSense continue to innovate and scale its market intelligence capabilities.

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Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в alphasense уже сейчас

Присоединяйтесь к AlphaSense, чтобы возглавить разработку ИИ-платформы нового поколения и определять будущее финансовой аналитики!

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:

We are seeking a Principal Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers.

This role owns the self-sourcing and extraction foundation used by multiple teams across the organization. Today, human validation is used as a safety net. Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability.

You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems.

Who You Are:

  • 15+ years of experience building and operating large-scale production systems
  • Proven experience designing data ingestion, extraction, or processing systems at scale
  • Deep expertise in one or more of:

+ Distributed systems

+ Data platforms and pipelines

+ AI/ML-powered extraction or classification systems

+ Platform or infrastructure engineering

  • Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
  • Strong understanding of system reliability, observability, failure modes, and iterative hardening
  • Experience reducing operational or human overhead through better system design
  • Track record of technical leadership across teams without formal people management
  • Comfortable operating in ambiguity and driving clarity where none exists
  • Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems
  • Nice to Have

+ Experience with document understanding, NLP, or financial data extraction

+ Experience building provenance, lineage, or confidence-scoring systems

+ Familiarity with cloud-native architectures and modern data stacks

+ Experience shaping or owning internal platforms used by multiple teams

What You’ll Do: 

  • Own the architecture and evolution of our large-scale data extraction and normalization platform
  • Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability
  • Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards
  • Establish clear system contracts for correctness, traceability, and confidence (e.g., “where did this number come from?”)
  • Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity
  • Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary
  • Partner with product and downstream consumers to define quality bars, SLAs, and success metrics
  • Serve as a technical escalation point for production issues, reliability failures, and systemic risks
  • Mentor senior engineers, shape technical culture, and raise expectations for system design and execution
  • Contribute to long-term technical strategy while remaining hands-on with critical implementations

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

$202,000—$278,000 CAD

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.

+400% к собеседованиям

Создайте идеальное резюме с помощью ИИ-агента

Создайте идеальное резюме с помощью ИИ-агента

Навыки

  • Distributed Systems
  • Data Pipelines
  • Artificial Intelligence
  • Machine Learning
  • System Architecture
  • Scalability
  • Observability
  • NLP
  • Cloud Native
  • Data Quality

Возможные вопросы на собеседовании

Вакансия подразумевает работу с огромными объемами данных из разных источников. Важно понять, как кандидат обеспечивает надежность при масштабировании.

Опишите ваш опыт проектирования систем обработки данных, которые масштабируются до сотен тысяч записей из разнородных источников (PDF, HTML, API). С какими узкими местами вы сталкивались?

Ключевая задача роли — уменьшение участия человека в проверке данных. Вопрос проверяет умение строить системы доверия.

Как бы вы спроектировали систему оценки уверенности (confidence scoring) для данных, извлеченных с помощью ИИ, чтобы минимизировать ручную валидацию без потери качества?

Для финансовых данных критически важно знать происхождение каждой цифры.

Каков ваш подход к реализации прослеживаемости данных (data lineage) и прозрачности (explainability) в гибридных ИИ-системах?

Позиция Principal Engineer требует влияния на архитектуру без прямого управления людьми.

Приведите пример, когда вам приходилось блокировать неудачное архитектурное решение или инициировать полный редизайн критической системы. Как вы аргументировали свою позицию?

Работа с ИИ требует понимания рисков и методов их минимизации.

Как вы балансируете между использованием инновационных ИИ-подходов и проверенных детерминированных правил в контексте обеспечения SLA и надежности системы?

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alphasense
Страна
Канада
Зарплата
202 000 CA$ – 278 000 CA$