- Страна
- США
- Зарплата
- 149 200 $ – 214 500 $
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AI Product Engineer
Отличная вакансия в быстрорастущей AI-компании с высокой прозрачностью процессов и прямым влиянием на бизнес. Высокая зарплата, удаленный формат работы в США и возможность работать на острие технологий AI-агентов.
Сложность вакансии
Роль требует не только глубоких технических знаний в области LLM и Python, но и сильных продуктовых навыков. Высокий темп разработки (еженедельные демо) и необходимость работать автономно делают позицию сложной, но интересной для опытных разработчиков.
Анализ зарплаты
Предложенный диапазон ($149k - $215k) полностью соответствует рыночным стандартам для Senior/Staff AI Engineer в США. Нижняя планка выше среднего по рынку для специалистов с опытом от 2 лет, что делает предложение очень конкурентоспособным.
Сопроводительное письмо
I am writing to express my strong interest in the AI Product Engineer position at Abnormal Security. With a solid background in building and deploying LLM-based agents into production environments, I am particularly drawn to your team's focus on shipping real products at a weekly cadence. My experience aligns perfectly with your need for an engineer who can bridge the gap between platform infrastructure and direct product delivery.
In my previous projects, I have focused on creating scalable AI workflows and integrating complex APIs to empower non-technical stakeholders. I am proficient in Python and have a deep understanding of agentic frameworks, which allows me to build the tools and connectors necessary for sophisticated AI operations. I thrive in high-autonomy environments and am eager to contribute to a 700-person GTM organization where my work has a direct line-of-sight to the CEO’s priorities.
I am impressed by Abnormal Security's commitment to AI-native systems and the high-visibility nature of this role. I look forward to the possibility of demoing my work every Friday and helping the AI Transformation Engineering team accelerate its product workstreams.
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Описание вакансии
About the Role
Abnormal Security is building AI-native systems that transform how enterprise GTM teams operate — and we're doing it by shipping real products on a weekly cadence.
The AI Transformation Engineering team is the infrastructure layer that makes this possible: we build and maintain the platforms, integrations, and tooling that power a growing fleet of AI agents operating across Sales, Customer Success, and Marketing.
As an AI Product Engineer, you'll work at the intersection of platform engineering and direct product delivery. Some weeks you're extending agent infrastructure — building new tools, connectors, and APIs that let AI agents do things they couldn't do before. Other weeks you're shipping GTM tooling directly, moving fast because the shortest path to impact is writing the code yourself.
You'll collaborate closely with AI Product Managers who define and build automations weekly, unblocking them with new platform capabilities and partnering on what to build next.
This is a high-visibility, high-autonomy role. You'll demo your work every Friday. Your systems will be used by a 700-person GTM org. You'll work closely with engineering and product leadership and have line-of-sight to the CEO’s priorities.
What You Will Do
- Build and extend agent platform capabilities — new tools, APIs, data connectors, and integrations that expand what AI agents can do without manual intervention
- Ship self-serviceable GTM tooling that enables non-technical users to set up their own AI-initiated LLM workflows.
- Partner with AI Product Managers on platform requirements — translate their roadmap blockers into well-scoped engineering deliverables with reliable timelines
- Identify and build reusable infrastructure — proactively design horizontal capabilities that accelerate multiple product workstreams at once
- Own reliability and observability for the systems you build — you're not handing off to an ops team
- Demo your work weekly and communicate clearly to technical and non-technical stakeholders alike
The Ideal Candidate
You're an engineer who ships things. You've built LLMs and agents in production — not as a side experiment, but as the core of what you were delivering. You have strong product instincts alongside engineering depth: you ask "who is this for and what do they actually need?" before writing code. You move fast without being careless, and you use AI coding tools as force multipliers, not crutches.
You're motivated by ownership and velocity. You'd rather have a small surface area and full accountability than a large team and a ticket queue.
Must Haves
- 2+ years of software engineering experience (strong internship and project portfolios considered)
- Demonstrated experience building with LLMs, agents, or AI APIs in a real product context — show us something that shipped
- Proficiency in Python; comfort picking up new frameworks quickly
- Experience integrating external APIs and building data pipelines
- Strong written communication — you can write a clear spec and a clear async update
- Ability to work with high autonomy, minimal oversight, and surface blockers proactively
Nice to Have
- Frontend or full-stack experience (React/Next.js) for building internal tools and dashboards
- Familiarity with agentic frameworks (LangGraph, CrewAI, Autogen) or production-scale prompt engineering
- Prior experience in a startup or high-velocity small team
- Open source contributions or a public portfolio of AI projects
#LI-ML1
Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.
In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.
Base salary range:
$149,200—$214,500 USD
Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
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Навыки
- Python
- LLM
- AI Agents
- APIs
- Data Pipelines
- React
- Next.js
- LangGraph
- CrewAI
- Autogen
- Prompt Engineering
Возможные вопросы на собеседовании
Проверка практического опыта работы с LLM и понимания проблем продакшена.
Расскажите о самом сложном случае внедрения LLM-агента в реальный продукт: с какими проблемами галлюцинаций или задержек вы столкнулись и как их решили?
Оценка навыков проектирования систем и интеграции данных.
Как бы вы спроектировали масштабируемую систему коннекторов для интеграции AI-агентов с внешними CRM-системами (например, Salesforce)?
Проверка продуктового мышления и умения приоритизировать задачи.
Если AI Product Manager просит функционал, который технически сложно реализовать в текущей архитектуре, как вы будете искать компромисс между скоростью поставки и качеством кода?
Оценка опыта работы с современными фреймворками.
Какие преимущества и недостатки вы видите в использовании LangGraph или CrewAI по сравнению с написанием собственной логики управления агентами?
Проверка навыков обеспечения надежности (Observability).
Как вы организуете мониторинг и отладку цепочек LLM в продакшене, чтобы быстро находить причины сбоев в логике агента?
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- Страна
- США
- Зарплата
- 149 200 $ – 214 500 $