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SeniorВ офисеПолная занятость

Senior Software Engineer (AI Applications)

Оценка ИИ

Отличная вакансия в стабильной компании-единороге с сильным технологическим стеком. Работа над передовыми AI-продуктами для финансового сектора и использование современных инструментов (LLM, LangChain, Kubernetes) делают эту позицию крайне привлекательной для профессионального роста.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена требованием глубокой экспертизы как в классическом программном обеспечении (6+ лет Python), так и в специфических AI-технологиях (LLM, Prompt Engineering, Langfuse). Роль подразумевает полную ответственность за жизненный цикл продукта, включая on-call поддержку и масштабирование конвейеров данных.

Анализ зарплаты

Медиана45 000 $
Рынок35 000 $ – 60 000 $
Оценка ИИ

Зарплата для Senior AI Engineer в Пуне (Индия) обычно выше среднего по рынку из-за дефицита специалистов по LLM. Указанный диапазон отражает текущие рыночные реалии для международных продуктовых компаний в этом регионе.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Software Engineer (AI Applications) position at AlphaSense. With over 6 years of experience in Python development and a specialized focus on deploying LLM-based solutions, I am confident in my ability to contribute to your Content Engineering team's mission of transforming complex document processing.

In my previous roles, I have successfully implemented data extraction pipelines using LangChain and FastAPI, focusing on structured JSON extraction and prompt optimization. I have extensive experience with LLM observability tools like Langfuse and a deep understanding of managing non-deterministic outputs in production environments. My background in processing large-scale datasets aligns perfectly with AlphaSense’s scale and the technical challenges described in the job posting.

I am particularly drawn to AlphaSense because of your leadership in market intelligence and the sophisticated way you integrate AI into decision-making processes. I look forward to the possibility of bringing my expertise in NLP and microservices architecture to your team to help unearth even more comprehensive insights for your enterprise customers.

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Откликнитесь в alphasense уже сейчас

Присоединяйтесь к AlphaSense, чтобы создавать передовые AI-решения для анализа финансовых рынков и работать с LLM на промышленном уровне!

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:

Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity.

Requirements:Must have

  • 6+ years of experience as a software engineer, primarily with Python
  • Ideally, you possess an advanced degree (Bachelor's / Master's)  in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered
  • 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs).
  • Experience in extracting structured JSON from text using LLMs and a deep understanding of Prompt Engineering.
  • Proficiency in classic NLP libraries for tasks like NER, text classification, and pre-processing.
  • Experience with LLM tracing, debugging and evaluation platforms such as Langfuse.
  • Excellent communication, organizational, problem-solving, debugging, and analytical skills.

Great to have

  • Experience in async processing of data at scale
  • Using frameworks like LangChain, HuggingFace, and backend web frameworks like FastAPI.
  • Expertise on core engineering skills - Cloud, microservice architecture, caching, and queuing.
  • Familiarity with concepts/tools as Docker, k8s, VCS, CI/CD
  • Previous experience in data extraction from specific domains (e.g., financial reports, news).

Responsibilities:

  • Deploy LLM based production grade solutions.
  • Fine-tune and adapt State of the art LLMs for specialized data extraction tasks. Develop innovative prompt engineering strategy and systems to maximize reliability and performance on confidential business documents.
  • Solve Engineering challenges that come along with LLM solutions, such as high latency, non-deterministic output, etc.
  • Implement and scale data processing pipelines that can process high volumes of complex documents with high accuracy and efficiency.
  • Integrate and manage LLM Observability to trace, debug, and monitor every extraction
  • Own systems end-to-end, including(but not limited to) designing, coding, monitoring, testing, CI/CD and on-call support.

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

  • Python
  • NLP
  • LLM
  • Prompt Engineering
  • LangChain
  • Huggingface
  • FastAPI
  • Docker
  • Kubernetes
  • Microservices
  • CI/CD
  • JSON
  • Langfuse
  • NER

Возможные вопросы на собеседовании

Проверка опыта работы с нестабильностью LLM в продакшене.

Как вы справляетесь с проблемой недетерминированности ответов LLM при извлечении структурированных данных (JSON)?

Оценка навыков мониторинга и отладки AI-систем.

Расскажите о вашем опыте использования Langfuse или аналогичных платформ для трассировки и оценки качества работы моделей.

Проверка архитектурных навыков при работе с большими данными.

Как бы вы спроектировали систему обработки документов с высокой задержкой (high latency) от LLM, чтобы обеспечить масштабируемость?

Оценка практического опыта в Prompt Engineering.

Какие стратегии промпт-инжиниринга вы использовали для минимизации галлюцинаций при анализе финансовых отчетов?

Проверка навыков работы с асинхронностью и бэкендом.

В чем преимущество использования FastAPI и асинхронности при интеграции внешних AI API?

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