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1 месяц назад

Senior Backend Engineer (AI)

Тип работы
fulltime
Грейд
senior
Английский
b2
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Backend Engineer (AI): Building a secure, scalable Notes Execution Platform for supply chain AI with an accent on sandboxing, resource management, and distributed job orchestration. Focus on designing isolated execution environments, developing backend APIs for job lifecycles, and integrating the platform with ML workflows.

Company

hirify.global is an enterprise AI platform built specifically for supply chain optimization, empowering Fortune 500 companies to leverage decision intelligence through out-of-the-box AI solutions and a composable platform.

What you will do

  • Design and scale the Notes Execution Platform to enable secure and observable execution of internal and external code.
  • Architect sandboxed environments to run untrusted user code with strict security controls and resource quotas.
  • Develop backend services and APIs to manage job lifecycles, including scheduling, monitoring, cancellation, and logging.
  • Ensure the system is resilient and capable of horizontal scaling to meet growing demand.
  • Integrate the execution platform with hirify.global's data platform and ML workflows.
  • Collaborate with product managers and data scientists to deliver an intuitive developer experience.

Requirements

  • 5+ years of backend engineering experience, ideally building distributed systems or platform infrastructure.
  • Deep expertise in Python, Go, or Java, and experience designing RESTful or gRPC APIs.
  • Proficiency with containerization and orchestration technologies such as Docker and Kubernetes.
  • Strong understanding of secure code execution, sandboxing, and resource quota enforcement.
  • Familiarity with distributed job queues and task orchestration systems like Celery, Airflow, or Kubernetes Jobs.
  • Proven track record of building performant, resilient, and observable systems at scale.

Nice to have

  • Experience building notebook-like platforms such as JupyterHub or Databricks.
  • Exposure to data and ML platforms and their specific execution requirements.
  • Experience with multi-tenant systems and securing shared infrastructure.

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