Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Очень мало
147к-197к CAD/год
200к CAD250к CADмедиана310к CAD
По похожим ролям (50) ~ 250к CAD/год
На СНГ рынке: $2.9к/мес ($2.6к - $3.7к)
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Сильная позиция Staff-инженера в глобальном гиганте с миксом современного SRE и передовых AI-инструментов, хотя зарплата ниже рыночной медианы, а смены на онколле довольно тяжелые.
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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