Назад
2 дня назад

Solution Engineer (AI)

165 000 - 216 562$
Тип работы
fulltime
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Solution Engineer (AI) (Data Architecture/Generative AI): Guiding customers from raw data to AI impact by architecting scalable data and AI solutions, delivering demos, and supporting enterprise proofs of concept with an accent on SQL, Python, modern data warehousing, and executive communication. Focus on leading AI strategy conversations, translating complex technical concepts into measurable business outcomes, and navigating high-stakes enterprise sales cycles.

Location: US-NY-New York

Salary: $165,000–$216,562 per year

Company

Snowflake provides modern data architecture and AI capabilities for enterprise customers.

What you will do

  • Partner with Sales to guide customers from raw data to measurable AI impact.
  • Lead customer conversations focused on AI strategy and data modernization.
  • Design and demonstrate scalable data and AI solutions using SQL and Python.
  • Support enterprise proofs of concept from initial concept through value realization.
  • Translate complex technical concepts into measurable business outcomes for technical and executive audiences.
  • Navigate objections, competitive dynamics, and complex buying decisions during high-stakes sales cycles.

Requirements

  • Strong SQL proficiency and experience with modern data warehousing.
  • Experience using Python for analytics or machine learning workflows.
  • Familiarity with AI/ML concepts, including Generative AI and LLMs.
  • Exceptional communication skills across technical and executive audiences.
  • Ability to influence stakeholders and maintain credibility under pressure.
  • Growth mindset with a track record of learning and adapting quickly.

Culture & Benefits

  • AI tools are used to personalize demos, accelerate preparation, and enhance delivery.
  • Work in a dynamic, fast-moving environment with an experimental mindset.
  • Contribute to a culture that values low-ego collaboration, innovation, and challenging ordinary thinking.
  • Follow company confidentiality and security standards when handling sensitive customer data.

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