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обновлено 5 дней назад

Staff Engineer, Site Reliability Engineering (AI)

147 000 - 196 600CAD
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Canada
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
Staff Engineer, Site Reliability Engineering (AI): Building reliable, observable, operable, and scalable infrastructure for vehicle telemetry, data ingestion, and software-defined vehicle data platforms with an accent on production readiness, CI/CD, observability, and AI-assisted operational workflows. Focus on designing fault-tolerant systems, automating incident response, leading on-call mitigation, and driving durable reliability improvements across engineering teams.

Location: Hybrid in Markham, Ontario; reporting to the Markham office at least three times per week. Weekly on-call rotation includes 12-hour shifts, cycling every eight weeks.

Salary: CAD 147,000–196,600 per year. hirify.global does not provide immigration-related sponsorship for this role.

Company

hirify.global is developing a next-generation Software-Defined Vehicle platform focused on connected vehicles, safety, personalization, energy optimization, and operational decision-making.

What you will do

  • Lead the design and implementation of scalable, fault-tolerant, and observable infrastructure for vehicle telemetry, data ingestion, and platform operations.
  • Drive production readiness across teams through hands-on coding, reliability standards, resilient deployments, observability, and predictable operations.
  • Design and improve CI/CD pipelines with quality gates, artifact promotion, deployment verification, progressive delivery, and rollback practices.
  • Define SLOs, SLIs, monitoring, alerting, runbooks, and operational practices with SRE, product, application, data engineering, infrastructure, and developer experience teams.
  • Build reusable AI workflows and evaluations, automate incident intake, triage, diagnostics, remediation, evidence collection, service requests, and customer-facing status workflows.
  • Lead incident response, post-incident reviews, durable system-level fixes, customer collaboration, technical direction, mentoring, and engineering standards across teams.

Requirements

  • 8+ years of experience in SRE, DevOps, or systems engineering, including managing or mentoring high-impact teams.
  • Experience designing, building, and maintaining high-scale cloud-native production systems, preferably on Azure, AWS, or GCP.
  • Hands-on experience with observability architecture, standardized instrumentation, OTEL Collector configuration, SLO/SLI definitions, monitors, alerts, and dashboards.
  • Strong understanding of production readiness, service ownership, SLOs, incident management, post-incident learning, and continuous reliability improvement.
  • Experience participating in on-call rotations and leading technical responses to production incidents.
  • Experience designing, operating, and improving CI/CD pipelines; knowledge of GitOps, release strategies, quality gates, deployment verification, progressive delivery, and safe rollback.
  • Strong programming ability in Python, Go, Java, or a comparable language, with disciplined code review, version control, testing, and maintainability practices.
  • Familiarity with AI-assisted software development, LLM application practices, agentic workflows, and evaluation techniques.
  • Ability to work professionally and empathetically with internal customers in difficult or high-pressure situations, influence without formal authority, and communicate with technical and non-technical audiences.
  • Strong ownership, judgment, accountability, and ability to operate at pace in a high-velocity environment.
  • BS, MS, or PhD in computer science, engineering, physics, mathematics, or another relevant technical field.

Nice to have

  • Azure Databricks, Azure Event Hubs, and Azure Kubernetes Service.
  • Kubernetes configuration management with Helm and Kustomize; infrastructure as code with Terraform.
  • GitHub Actions, Argo CD, and GitOps-based deployment models.
  • Prometheus, Grafana, Datadog, OpenTelemetry, or comparable observability tools.
  • LLM application development and testing with Promptfoo, agentic workflows, and reusable AI skills with Copilot.
  • Large-scale data ingestion, processing, and delivery systems such as Fivetran, Apache Flink, Kafka, and Pulsar.
  • Vehicle telemetry, connected-vehicle platforms, or other high-volume event-driven systems.

Culture & Benefits

  • Hybrid work with regular office presence in Markham and participation in an on-call rotation.
  • Paid time off, vacation days, holidays, and supplemental pregnancy, parental, and adoption leave.
  • Healthcare, dental, vision, and life insurance benefits.
  • Defined Contribution Pension plan with company matching contributions.
  • GM Vehicle Purchase Plan for employees and their families.
  • Focus on sustainability, inclusive innovation, and the future of mobility.

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