aijavapythonkubernetesbackenddockerdevopsterraformmachine learningdistributed systems
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Это достаточно чётко описанная senior-позиция в платформенной команде AI-продукта с задачами по инфраструктуре и ML в production; отдельно стоит уточнить требование к облачным платформам.
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior/Staff Platform Software Engineer (AI): Building and scaling secure backend services and core infrastructure for an enterprise AI agent platform with an accent on automation, observability, reliability, and performance. Focus on designing distributed systems, operating ML/NLP workloads in production, and leading architecture, infrastructure, and developer-experience improvements.
Location: US Remote
Company
hirify.global provides an enterprise AI agent and RAG platform focused on retrieval, embeddings, reranking, LLM quality, hallucination mitigation, security, accuracy, and explainability. The platform serves enterprise customers across military, financial services, healthcare, and manufacturing.
What you will do
Design, implement, and maintain scalable, secure backend services and platform components.
Lead code, system design, and architecture reviews while mentoring team members.
Drive infrastructure automation, CI/CD, monitoring, and alerting pipelines.
Collaborate with product engineering and research teams to deploy, scale, and optimize ML/NLP workloads.
Lead initiatives improving reliability, scalability, developer experience, code quality, testing, and DevOps practices.
Use AI-assisted coding, manage multiple tasks, and coordinate AI agents effectively.
Requirements
5+ years of software engineering experience focused on backend systems and platform engineering.
Proficiency in Java and Python.
Deep experience with computing environments including GCP, AWS, on-premises, or Azure.
Strong understanding of containerization and orchestration with Docker and Kubernetes.
Experience with infrastructure as code, such as Terraform or Pulumi.
Experience with observability tools such as Prometheus, Grafana, and ELK/EFK.
Experience working on ML platforms or supporting ML workloads in production.
Experience designing and operating distributed systems.
Familiarity with data infrastructure such as Kafka, Spark, or Airflow.
100% company-paid medical, dental, and vision coverage begins on the first day.
Health Savings Account or Flexible Spending Account options.
Paid time off, paid sick time, holidays, and company rest days.
Professional development and training opportunities, plus virtual team-building activities.
Supportive, inclusive culture focused on curiosity, humility, hard work, inventiveness, and continuous improvement.
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