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arizeai
Страна
США
Зарплата
125 000 $ – 175 000 $
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AI Solutions Engineer (Charlotte)

Оценка ИИ

Высокий балл обусловлен работой в одной из самых перспективных ниш (AI Observability), отличным финансированием компании (Series C) и конкурентной зарплатой с опционами. Удаленный формат работы с бонусами на коворкинг также является большим плюсом.


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Оценка ИИ

Роль требует редкого сочетания глубоких технических знаний в области LLM/ML и отличных навыков общения с клиентами. Кандидат должен разбираться в инфраструктуре (Kubernetes, Cloud) и одновременно уметь проводить стратегические бизнес-ревью.

Анализ зарплаты

Медиана155 000 $
Рынок130 000 $ – 190 000 $
Оценка ИИ

Предлагаемая зарплата ($125k - $175k) полностью соответствует рыночным ожиданиям для опытных Solutions-инженеров в США, специализирующихся на AI. Наличие опционов (equity) значительно повышает общую ценность предложения.

Сопроводительное письмо

I am writing to express my strong interest in the AI Solutions Engineer position at Arize AI. With a solid background in Machine Learning and experience working with LLM frameworks like LangChain and LlamaIndex, I have seen firsthand the critical need for robust observability and evaluation tools in production environments. Your recent Series C funding and work with industry giants like Uber and Siemens demonstrate that Arize is at the forefront of solving the most pressing challenges in the GenAI space.

In my previous roles, I have successfully bridged the gap between complex technical implementations and business value, a skill I look forward to bringing to your Solutions Engineering team. I am particularly impressed by Arize's commitment to responsible AI and bias mitigation. I am eager to leverage my expertise in Python and cloud environments to help your customers optimize their AI agents and ship high-performing applications with confidence.

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Присоединяйтесь к лидеру в области AI-обсервабильности и помогайте крупнейшим компаниям мира внедрять надежные генеративные модели!

Описание вакансии

About Arize

AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.

We’re a Series C company backed by top-tier investors,withover $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies.Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.

The Team

Our engineering team builds systems that interact with some of the most complex software  ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. 

We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize.

What You’ll Do

  • Work closely with some of the most sophisticated ML / GenAI teams in the world.

+ You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.

  • Advise on GenAI and ML best practices
  • Give ML and LLM product demos to technical and business stakeholders
  • Run strategic business reviews for customers in partnership with our sales team
  • Interface with our pre-sales engineering team to gather client goals and KPI’s.
  • Partner with our product and engineering teams to help drive the product roadmap
  • Spearhead new opportunities within existing accounts to help drive expansions.

What We’re Looking For

Note: Even if you do not check every single box, we still encourage you to apply!

  • Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
  • Comfortable working in public Cloud environments (AWS, Azure, GCP)
  • Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
  • Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
  • Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
  • Understanding of GenAI concepts and application evaluation + development lifecycle
  • Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
  • Strong Communication Skills - Ability to simplify complex, technical concepts.
  • A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Bonus Points, But Not Required

  • Previous engineering experience in:

+ Data Science

+ MLOps

+ ML Frameworks

+ LLM / Agentic frameworks

  • Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
  • Prior experience working with applications deployed with Kubernetes
  • Prior experience demoing technical products to both business and technical audiences

The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

This role requires the right candidate to be based in Raleigh, New York City, or San Francisco

More About Arize

Arize’s mission is to make the world’s AI work—and work for people.

Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale.

Learn more about what we're doing here:

https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/

https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/

Diversity & Inclusion @ Arize

Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture

  • Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
  • Culturally conscious events such as LGBTQ trivia during pride month
  • We have an active Lady Arizers subgroup
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Навыки

  • Python
  • Machine Learning
  • Generative AI
  • LLM
  • LlamaIndex
  • LangGraph
  • DSPy
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • AWS
  • Azure
  • GCP
  • Kubernetes
  • REST API
  • MLOps

Возможные вопросы на собеседовании

Проверка практического опыта работы с жизненным циклом LLM-приложений.

Расскажите о самом сложном случае отладки LLM-агента в продакшене: какие метрики вы использовали и как нашли причину галлюцинаций?

Оценка навыков работы с клиентами и умения объяснять сложные вещи просто.

Как бы вы объяснили техническую ценность платформы обсервабильности Arize финансовому директору (CFO), который не разбирается в коде?

Проверка знаний современных фреймворков, упомянутых в вакансии.

В чем, по вашему мнению, основные различия в подходах к оценке (evaluation) между традиционным ML и современными Agentic-системами на базе DSPy или LangGraph?

Оценка опыта работы с облачной инфраструктурой.

Опишите ваш опыт развертывания ML-моделей в Kubernetes: с какими проблемами масштабирования вы сталкивались?

Проверка проактивности и навыков продаж внутри аккаунта.

Если вы заметили, что клиент использует Arize только для базового мониторинга, как вы построите разговор, чтобы убедить их внедрить продвинутые функции оценки (evaluation)?

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arizeai
Страна
США
Зарплата
125 000 $ – 175 000 $