- Страна
- Канада
- Зарплата
- 160 000 ₽ – 220 000 ₽
Откликайтесь
на вакансии с ИИ

Senior AI Engineer, AI Platform
Высокая оценка обусловлена прозрачным диапазоном зарплаты, удаленным форматом работы и возможностью работать с передовыми технологиями (LLM, агенты) в успешной компании. Affinity имеет отличную репутацию и награды как лучший работодатель.
Сложность вакансии
Роль требует глубоких знаний в области LLM, RAG-систем и MLOps, а также более 5 лет опыта. Высокая сложность обусловлена необходимостью работы с миллиардами точек данных и созданием сложных мультиагентных систем.
Анализ зарплаты
Предлагаемая зарплата в 160,000–220,000 CAD полностью соответствует рыночным ожиданиям для Senior AI ролей в Канаде, находясь на уровне или чуть выше медианы для высокотехнологичных продуктовых компаний.
Сопроводительное письмо
I am writing to express my strong interest in the Senior AI Engineer position at Affinity. With over five years of experience in software engineering and a deep focus on deploying machine learning models in production, I am particularly drawn to your team's work on building RAG pipelines and multi-agent LLM systems. My background in architecting hybrid retrieval systems and optimizing context windows aligns perfectly with Affinity's mission to extract actionable insights from complex professional relationship data.
In my previous roles, I have successfully implemented LLM-powered search and entity extraction tools, utilizing vector databases and rigorous evaluation metrics like hallucination rates and factual consistency. I am impressed by Affinity's commitment to a data-driven culture and quick iteration, and I am eager to bring my expertise in MLOps and prompt engineering to help scale your industry-leading relationship intelligence platform. I look forward to the possibility of contributing to your cross-functional team and driving innovation in the private capital sector.
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Откликнитесь в affinity уже сейчас
Присоединяйтесь к Affinity, чтобы создавать передовые RAG-системы и определять будущее CRM-платформ для частного капитала!
Описание вакансии
Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network.
This role is part of the AI Platform team, which owns the AI services that power Affinity's industry-leading relationship intelligence platform. We extract and retrieve information from billions of structured and unstructured data points to deliver actionable insights to customers.
As a Senior AI Engineer, you will collaborate with machine learning engineers, data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will design and build LLM-powered AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry.
In this role you will:
- Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques.
- Build LLM powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers.
- Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data.
- Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) to build robust, high-scale systems that underlie all of our data processing and ML Operations.
Qualifications
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Required:
- 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
- Hands on experience with LLM applications in production including prompt engineering and utilizing frameworks for online and offline evaluation
- Experience with LLM assisted search, such as query understanding and augmentation, text2sql, and entity extraction
- Experience with vector or graph databases
- Experience with document chunking, embedding models, and context window optimization
- Familiarity with metadata-based retrieval and re-ranking strategies
- Hands on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)
- Familiarity with data security, versioning, and MLOps principles
Nice to Have:
- Experience with enterprise AI applications with strict compliance, audit, or legal requirements
- Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvements.
- Experience with multi-modal search
- Experience with graph based recommendation systems, such as graph NN.
- Experience with developing AI applications powered by agent-based systems
- Experience with packaging, CI/CD and pipeline automation.
Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference.
How we work:
Our culture is a key part of how we operate, as well as our hiring process:
- We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
- We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with.
- We make data-driven decisions and make the best decision for the moment based on the information available.
If you’d want to learn more about our values click here.
What you'll enjoy at Affinity:
- We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
- Health Benefits: We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
- Retirement Planning: We offer an RRSP plan to help you plan for your future.
- Learning & Development: We provide an annual education budget and a comprehensive L&D program.
- Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
- Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.
Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.
A reasonable estimate of the current range is $160,000 to $220,000 CAD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.
At Affinity, we may use artificial intelligence (AI) tools as part of our recruitment process to help screen and evaluate candidate applications. While AI assists our hiring team in managing applications efficiently, it never replaces decisions made by real people. We are committed to fair and transparent hiring practices, and our AI tools are regularly monitored to ensure they support—not replace—human judgment.
Additional Information:
- This job posting represents an active vacancy that we are currently seeking to fill.
About Affinity
With more than 3,000 customers worldwide and backed by some of Silicon Valley's best firms, Affinity has raised $120M to empower dealmakers to find, manage, and close more deals. How? Our Relationship Intelligence platform uses the wealth of data exhaust from trillions of interactions between Investment Bankers, Venture Capitalists, Consultants, and other strategic dealmakers to deliver automated relationship insights that drive over 450,000 deals every month. We are are proud to have received Inc. and Fortune Best Workplaces awards as well as to be Great Places to Work certified for the last 5 years running. Join us on our mission to make it possible for anyone to cultivate and fully harness their network to succeed.
We use E-Verify
Our company uses E-Verify to confirm the employment eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- Machine Learning
- LLM
- CI/CD
- MLOps
- RAG
- Vector Database
- Graph Database
- Prompt Engineering
- Information Retrieval
- NLP
Возможные вопросы на собеседовании
Проверка практического опыта работы с RAG-системами, что является ключевой задачей в данной роли.
Расскажите о наиболее сложной RAG-системе, которую вы проектировали. С какими проблемами при поиске и ранжировании вы столкнулись и как их решили?
Вакансия требует опыта работы с метриками оценки моделей.
Как вы подходите к оценке галлюцинаций и фактической согласованности в LLM-приложениях перед их деплоем в продакшн?
В описании упоминается работа с мультиагентными системами.
Какие фреймворки для оркестрации агентов вы использовали и в каких случаях кастомный слой оркестрации предпочтительнее готовых решений?
Работа с большими данными требует оптимизации хранения и поиска.
Как вы выбираете между векторными и графовыми базами данных для конкретной задачи извлечения информации?
Affinity ценит умение работать в условиях неопределенности и быстро итерировать.
Опишите ситуацию, когда вам пришлось принимать архитектурное решение в условиях неполных данных или меняющихся требований. Каков был результат?
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- Страна
- Канада
- Зарплата
- 160 000 ₽ – 220 000 ₽