обновлено 10 дней назад
Product Engineer (Analytics as a Service)
123 800 - 230 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Product Engineer (Analytics as a Service) (Fullstack/SaaS): Building cloud-native analytics services across backend services, APIs, data pipelines, user interfaces, cloud infrastructure, and analytics capabilities with an accent on AI-assisted, specification-driven development and customer-focused delivery. Focus on designing scalable, secure, observable software, rapidly validating customer needs, and delivering high-quality production releases with strong automated test coverage.
Location: Rochester, NY, United States
Salary: 123800.00–230000.00 USD per year
Company
is a public precision-technology company, while its Qualitrol business develops monitoring and protection devices and information products for high-value electrical assets.
What you will do
- Design, develop, and maintain cloud-native analytics services.
- Build backend services, APIs, data pipelines, user interfaces, cloud infrastructure, and analytics capabilities.
- Apply AI-assisted, specification-driven practices across software design, coding, testing, documentation, troubleshooting, and code reviews.
- Work with Product Owner and Customer Success to understand customer needs, validate assumptions, prototype rapidly, incorporate feedback, and deliver frequent releases.
- Participate in architecture discussions, peer reviews, and continuous platform improvement.
- Collaborate with SaaS Architecture, DevOps, Customer Success, and commercial leadership.
Requirements
- 5+ years of professional software development experience.
- Experience developing SaaS applications and using cloud-native architectures.
- Strong full-stack development skills.
- Experience with Agile software delivery and fast-paced product organizations.
- Ability to build secure, reliable, observable, maintainable, well-tested, and highly scalable software.
Nice to have
- Microsoft Azure or AWS experience.
- Kubernetes and modern web frameworks.
- Distributed systems, industrial IoT, or data analytics platform experience.
- AI-assisted software development experience.
Culture & Benefits
- Approximately 10% travel, including periodic customer visits.
- Collaborative engineering culture focused on rapid execution and continuous learning.
- Success is measured through production quality, release cadence, automated test coverage, AI-assisted development adoption, customer adoption, and platform improvement.
- Equal opportunity employer committed to diversity and reasonable accommodations.
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