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AI Solution Architect-Generative AI & Large Language Models

Оценка ИИ

Высокая оценка обусловлена работой в глобальной инновационной компании с передовым стеком технологий (GenAI, LLM). Позиция архитектора предполагает высокий уровень ответственности, влияние на стратегию компании и работу с разнообразными индустриями.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует редкого сочетания глубоких знаний в области LLM/Generative AI и навыков системной архитектуры корпоративного уровня. Кандидат должен не только разбираться в моделях, но и уметь выстраивать процессы MLOps, управления рисками и напрямую взаимодействовать с бизнес-заказчиками.

Анализ зарплаты

Медиана200 000 $
Рынок170 000 $ – 230 000 $
Оценка ИИ

Зарплата в вакансии не указана, но для позиции AI Architect в Нью-Джерси/Нью-Йорке рыночные показатели являются одними из самых высоких в индустрии. Предлагаемый диапазон 170k-230k USD соответствует уровню Senior/Lead специалистов в области Generative AI в крупных технологических консалтинговых компаниях.

Сопроводительное письмо

I am writing to express my strong interest in the AI Solution Architect position at Orion Innovation. With a solid background in designing and deploying enterprise-grade machine learning systems, I have closely followed the evolution of Generative AI and Large Language Models. My experience aligns perfectly with your need for an architect who can not only design RAG-based systems and agentic workflows but also ensure they are governed by robust MLOps and responsible AI practices.

Throughout my career, I have successfully bridged the gap between complex technical AI research and practical business applications. I am particularly drawn to Orion's diverse portfolio across industries like financial services and telecommunications, where the strategic implementation of LLMs can drive significant transformation. I am confident that my technical depth in transformer architectures, combined with my ability to communicate effectively with senior stakeholders, will allow me to contribute immediately to your team's success.

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Присоединяйтесь к Orion Innovation и станьте архитектором будущего, внедряя передовые решения Generative AI для крупнейших мировых компаний!

Описание вакансии

Orion Innovation is a premier, award-winning, global business and technology services firm.  Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity.  We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.

Job Title:

AI Architect – Generative AI & Large Language Models

Overview

We are seeking an AI Architect specializing in Generative AI and Large Language Models (LLMs) to help design, deploy, and scale AI solutions for enterprise clients.

This role requires deep expertise in machine learning and data science, particularly in the design, evaluation, and operationalization of modern language models and generative AI systems.

The AI Architect will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices.

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Architecture & Solution Design

  • Design and architect enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
  • Define architecture for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
  • Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
  • Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

  • Provide deep technical expertise in:
  • Large Language Models (LLMs)
  • Transformer architectures
  • Generative AI techniques
  • Model evaluation and benchmarking
  • Design approaches for fine-tuning, prompt engineering, and model adaptation.
  • Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

  • Lead deployment of machine learning and GenAI systems into production environments.
  • Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
  • Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

  • Implement frameworks for:
  • AI governance
  • Model explainability
  • Transparency
  • Risk management
  • Ensure compliance with enterprise AI governance standards and regulatory expectations.
  • Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

  • Act as a trusted technical advisor to client stakeholders.
  • Clearly communicate complex AI concepts to executives, architects, and engineering teams.
  • Represent the company with credibility in technical and strategic discussions around AI adoption.
  • Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

  • Stay current with emerging developments in:
  • Generative AI
  • Large language models
  • AI agents and agentic architectures
  • AI infrastructure and tooling
  • Evaluate new research and technologies to determine their practical applicability in enterprise environments.
  • Help shape the organization’s AI strategy and technical direction.

Required Qualifications

  • Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
  • Strong expertise in machine learning fundamentals and modern generative AI technologies.
  • Proven experience designing and deploying AI/ML systems in production environments.
  • Deep knowledge of:
  • Large Language Models
  • Generative AI architectures
  • ML pipelines and model lifecycle management
  • Experience working with AI frameworks and ecosystems used for building GenAI applications.
  • Experience implementing AI governance, explainability, and responsible AI practices.
  • Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

  • Experience with agentic AI systems and orchestration frameworks.
  • Experience building RAG-based AI systems.
  • Familiarity with AI platform engineering and scalable AI infrastructure.
  • Contributions to AI research, open-source projects, or technical publications.
  • Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

  • Machine Learning & Data Science
  • Large Language Models (LLMs)
  • Generative AI systems
  • AI agents and agentic architectures
  • MLOps and model lifecycle management
  • AI governance and explainability

Professional Skills

  • Strong analytical and problem-solving capabilities
  • Excellent communication and presentation skills
  • Ability to simplify complex AI concepts for diverse audiences
  • Collaborative mindset and ability to work effectively within teams
  • Client-facing professionalism and credibility

Work Environment

  • Full-time in-office role with collaboration across engineering and client teams.
  • Weekly client visits for workshops, architecture discussions, and solution design sessions.
  • High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

  • Successfully architect and deliver production-grade AI systems.
  • Become a trusted AI advisor to both internal teams and client stakeholders.
  • Ensure responsible and governed adoption of AI technologies.
  • Help organizations translate GenAI innovation into real operational value.

Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.

Candidate Privacy Policy

Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, “Orion,” “we” or “us”) are committed to protecting your privacy. This Candidate Privacy Policy (orioninc.com) (“Notice”) explains:

  • What information we collect during our application and recruitment process and why we collect it;
  • How we handle that information; and
  • How to access and update that information.

Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.

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Навыки

  • Generative AI
  • Large Language Models
  • Machine Learning
  • Data Science
  • MLOps
  • Transformer Architecture
  • Retrieval-Augmented Generation
  • AI Governance
  • Distributed Systems
  • Software Architecture
  • Python

Возможные вопросы на собеседовании

Проверка практического опыта проектирования сложных систем на базе LLM.

Опишите ваш опыт проектирования архитектуры RAG (Retrieval-Augmented Generation) для крупного предприятия. С какими основными проблемами масштабируемости вы столкнулись?

Оценка понимания современных трендов и автономных систем.

Как бы вы подошли к проектированию агентской архитектуры (Agentic Workflows) для автоматизации многоэтапных бизнес-процессов? Какие фреймворки оркестрации вы бы выбрали?

Важный аспект для корпоративного сектора, упомянутый в вакансии.

Какие стратегии вы используете для обеспечения Responsible AI и минимизации галлюцинаций в продуктовых решениях на базе генеративных моделей?

Проверка навыков операционализации моделей.

Расскажите о вашем опыте внедрения LLMOps. Как вы организуете мониторинг качества ответов моделей и версионность промптов в продакшене?

Оценка навыков общения с клиентами.

Как вы объясните нетехническому топ-менеджменту разницу между дообучением (fine-tuning) модели и использованием RAG для решения их бизнес-задачи?

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