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Principal AI Platform Engineer
Исключительная позиция в стабильной, но быстрорастущей компании (Unicorn status) с фокусом на передовые технологии AI. Высокий уровень автономии, возможность влиять на архитектуру глобального продукта и работа с крупнейшими клиентами (S&P 500) делают эту вакансию очень привлекательной для топ-инженеров.
Сложность вакансии
Высокая сложность обусловлена требованием к огромному опыту (12+ лет) и необходимостью совмещать глубокие знания распределенных систем с современными AI-технологиями (LLM, RAG). Роль подразумевает не только разработку, но и стратегическое лидерство, а также менторство команды.
Анализ зарплаты
Предлагаемая роль Principal уровня в международной компании в Бангалоре предполагает зарплату значительно выше среднего по рынку Индии. Указанный диапазон соответствует топовым технологическим компаниям и включает в себя не только базовый оклад, но и значительный пакет бонусов/акций.
Сопроводительное письмо
I am writing to express my strong interest in the Principal AI Platform Engineer position at AlphaSense. With over 12 years of experience in architecting and operating large-scale distributed systems, I have a proven track record of transforming complex AI/ML innovations into reliable, production-grade platforms. My background in implementing robust CI/CD pipelines, Kubernetes-based microservices, and comprehensive observability strategies aligns perfectly with your mission to bring world-class engineering excellence to AlphaSense’s AI-powered systems.
Throughout my career, I have specialized in bridging the gap between cutting-edge research and stable engineering, ensuring that high-growth platforms maintain 99.9%+ uptime even under heavy load. I am particularly excited about the opportunity to mentor your talented engineering team and shape the technical roadmap for agentic systems that process thousands of requests per hour. I am confident that my pragmatic approach to architectural trade-offs and deep expertise in modern infrastructure will significantly contribute to AlphaSense’s continued growth and innovation in market intelligence.
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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 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:
- 12+ 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.
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
- Microservices
- Infrastructure as Code
- CI/CD
- Distributed Systems
- LLM
- RAG
- Vector Databases
- Python
- Observability
- Prompt Engineering
Возможные вопросы на собеседовании
Проверка опыта работы с высоконагруженными системами и понимания архитектурных компромиссов.
Опишите случай, когда вам пришлось перепроектировать распределенную систему для достижения доступности 99.9%+. С какими основными препятствиями вы столкнулись?
Оценка способности кандидата внедрять инженерную культуру в AI-команды.
Как вы подходите к внедрению практик CI/CD и автоматизированного тестирования в проекты, связанные с LLM и агентами, где результаты могут быть недетерминированными?
Проверка навыков отладки и работы с инцидентами.
Расскажите о самом сложном инциденте в продакшене, который вы расследовали. Какие инструменты обсервабельности вы использовали и как предотвратили повторение проблемы?
Оценка лидерских качеств и менторства.
Как вы подходите к менторству сильных инженеров и как помогаете команде расти профессионально, сохраняя при этом высокую скорость поставки продукта?
Проверка технических знаний в области AI-инфраструктуры.
Какие архитектурные паттерны вы считаете наиболее эффективными для масштабирования систем на базе AI-агентов, обрабатывающих тысячи запросов в час?
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