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Added 3 mins ago
EN
Principal Wireless SW Engineer
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- Full-time
The Principal Wireless Software Engineer is a senior technical leader responsible for resolving the most complex and business-critical customer issues escalated through the Global Technical…
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Added 1 hour ago
B
Software Engineer - Model Performance Systems
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Added 2 hours ago
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Added 4 hours ago
SF
Senior Site Reliability Engineer
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- Full-time
The Senior Site Reliability Engineer owns reliability, resilience and operational health across SafeFleet’s cloud-native product ecosystem. This is a hands-on engineering role with…
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W
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Senior WMS Implementation Engineer
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Safe Fleet

Senior Site Reliability Engineer

Coquitlam, BC, Canada

Salary Range: $120,000 - $145,000/yr · Full-time

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Job details

Pay: Salary Range: $120,000 - $145,000/yr
Job type: Full-time
Apply by: Oct 29, 2027
Posting language: English
Posted: Oct 29, 2026

Original job description

Meet The Smart Safety Company

At Safe Fleet our name says it all. We make fleet vehicles – and everyone in and around them – safer. Our fleet safety platform brings together best-in-class products, ground-breaking technology, and a 100-year history of fleet know-how and innovation to solve the world’s biggest fleet safety problems.

Our core value is safety. Without safety first, efficiency and productivity are not possible. This is true for our products, our culture, and our relationship with our community. Our vision is to reduce preventable deaths and injuries in and around fleet vehicles with a goal of ZERO accidents.

We are re-defining what safety means for fleets of every type – from school buses to waste collection trucks, firefighting to utility vehicles, police cruisers to delivery vans.

Whether you work in our Charlotte plant to build life-saving stop arms for school buses, or design advanced camera vision products in our Vancouver office, forge valves and high-quality nozzles to fight fires, or dream up new ways to protect fleet operators in our Corporate HQ in Kansas City, you’ll contribute to our goal to keep everyone safe.

We are a fast-growing manufacturing, service, and technology company with over 1700 employees in over 15 locations across Canada and the US. We’re looking for motivated self-starters with innovative thinking to join our team and help us achieve our growth and performance goals. Sound like you?

About The Role

The Senior Site Reliability Engineer owns reliability, resilience and operational health across SafeFleet’s cloud-native product ecosystem. This is a hands-on engineering role with practice-building responsibility: you will not simply operate within an existing reliability framework - you will design, define and mature it.

You will build the observability systems that detect problems before customers do, define and own the SLOs and error budgets for our core products, act as Incident Commander during critical events, and ensure post-incident remediation reaches production rather than ageing in a backlog. Safe Fleet is actively applying artificial intelligence to reliability engineering, and we expect this role to use AI as a core engineering tool - building SRE agents that triage and investigate, running AI-augmented war rooms, and automating the repetitive work of operations and reporting.

This is a Site Reliability Engineering role, not a DevOps or Platform Engineering role. CI/CD and infrastructure-as-code experience is valuable but is not the core of this job. We are looking for someone who has owned production reliability through real incidents, defined service level objectives, and changed how an engineering organisation behaves.

Responsibilities

Observability and Detection

Build, manage and continuously improve observability across metrics, logs, traces, alerts and dashboards.
Raise the proportion of incidents detected by monitoring before customer report, tracked as an explicit KPI.
Standardise monitoring coverage, working outside-in from customer-visible symptoms rather than from available metrics.
Own alerting maturity - alert TTL, ownership, labelling, routing, suppression, runbook linkage - while actively preventing alert fatigue.
Expand synthetic and workflow monitoring across critical user journeys, and apply AI-assisted anomaly detection and signal correlation to surface emerging failure patterns early.

Service Levels and Incident Management

Define and own SLIs, SLOs and error budgets, including negotiating targets with product and engineering stakeholders.
Establish and enforce error budget policy: what happens when a budget is exhausted, who is accountable, and how feature velocity is re-earned.
Act as Incident Commander during critical events - owning coordination, role assignment, stakeholder communication and the path to mitigation
Drive Root Cause Analysis and facilitate blameless post-incident reviews.
Track post-incident action items through to production - design the classification, ownership and escalation mechanism that guarantees remediation closes, and report on completion rates.
Coordinate L3 engineer schedules, validate escalation paths, and administer the incident management platform.
Lead SRE maturity initiatives: reliability scoring, observability maturity, roadmap execution and engineering enablement.
Own capacity planning and forecasting, and produce reliability reporting for both engineering teams and executive leadership.

AI in Reliability Engineering

A differentiating requirement for this role. We expect the Senior SRE to build and operate AI capability as part of the reliability practice, not to evaluate it theoretically.

SRE agents - design, build and operate AI agents that perform first-line triage, run diagnostic investigations across logs and traces, query observability systems, and propose or execute remediation under defined guardrails. Multi-agent and sub-agent patterns are strongly valued.
AI-augmented war rooms - use AI during live incidents to correlate telemetry, reconstruct timelines, summarise status for stakeholders and accelerate root cause identification.
AI-assisted postmortems - automate assembly of post-incident reports and generate candidate remediation work, including pull requests carrying incident context.
Process automation - apply AI to eliminate toil: runbook generation, alert tuning and noise reduction, capacity forecasting, reliability reporting and routine operational workflows.
Governance - define boundaries for autonomous action, human-in-the-loop checkpoints and auditability for AI-driven operational decisions.

Salary Range: $120,000 - $145,000/yr

The final offer will be determined based on a combination of factors including skills, experience, and alignment with the role’s responsibilities.

Candidates at the lower end of the range will meet the core qualifications and demonstrate strong potential to grow within the role.
Mid-range offers reflect a solid match with the role’s technical and collaborative requirements.
Offers at the top of the range are reserved for candidates who bring exceptional qualifications, specialized expertise, or unique value that significantly exceeds the baseline expectations

At Safefleet, we are an equal opportunity employer that is committed to creating a diverse and inclusive workplace where everyone is valued and respected. We embrace diversity and do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other legally protected status. We promote fair and equitable hiring practices and foster a culture of inclusivity and respect. Our core values of integrity, innovation, teamwork, customer focus, and safety guide our efforts to provide a workplace where all employees can thrive and reach their full potential.

Requirements:

Minimum 5 years in Site Reliability Engineering, Production Operations, Cloud Engineering or DevOps, with at least 3 years personally owning production reliability outcomes.
Demonstrated experience defining SLIs, SLOs and error budgets for distributed systems - not only operating against targets set by others.
Direct experience as Incident Commander or equivalent lead during severity-one production incidents.
Strong command of RCA methodology and blameless postmortem practice, including driving remediation to completion against competing product priorities.
Experience reducing toil through automation, with judgement about what is worth automating.
Hands-on production experience with Microsoft Azure and Azure Kubernetes Service (AKS) - our primary environment. Certification alone is not sufficient.
Strong expertise in observability systems, with hands-on experience across Grafana, Prometheus, Elasticsearch and APM tooling.
Experience with OpsGenie, PagerDuty or comparable incident management platforms, including on-call rotation design and escalation policy. Direct participation in an on-call rotation is a standard part of this role.
Strong scripting ability in Python, Bash or PowerShell for automation and workflow engineering.
Experience with capacity planning, forecasting and performance tuning.
Demonstrable, hands-on experience applying AI to operational engineering work. You should be able to walk us through something you built - an agent, an automation, an AI-assisted workflow - and explain what it consumed, what it decided, and what guardrails you placed around it.
Familiarity with agent frameworks, prompt engineering for operational contexts, and integration of AI into monitoring, incident or CI/CD workflows, with sound judgement about the limits of AI in production incident response.
Proven ability to influence engineering teams you do not manage, and to persuade product stakeholders to prioritise reliability work.
Experience designing operational processes and producing reliability KPI reporting for engineering and executive audiences.

Preferred

Experience building or maturing an SRE practice from an early baseline; chaos engineering and resilience testing; regulated, high-availability or safety-critical environments; sovereign or government cloud environments.

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More about this job

Responsibilities

Build and mature reliability practices across Safe Fleet’s cloud-native products, including observability, SLOs and error budgets, incident response, capacity planning, and reliability reporting. Develop AI-enabled operational capabilities such as triage agents, incident investigation workflows, postmortem automation, and toil reduction, with appropriate human oversight and safeguards.

Requirements

Requires at least five years in SRE, production operations, cloud engineering, or DevOps, including three years personally owning production reliability, plus experience defining SLOs and error budgets and leading severe incidents. Candidates need hands-on Azure and AKS experience, observability and incident-management expertise, scripting and capacity-planning skills, practical AI operations experience, and the ability to influence engineering and product stakeholders.

Skills

Site Reliability Engineering
Production Reliability
Observability
Incident Management
Incident Command
Service Level Objectives
Error Budgets
Root Cause Analysis
Blameless Postmortems
Microsoft Azure
Azure Kubernetes Service
Grafana
Prometheus
Elasticsearch
Python
Capacity Planning

Visa sponsorship

Not detected in the job text

Keywords

Site Reliability Engineering
SRE Practice
Cloud-Native Products
Microsoft Azure
Azure Kubernetes Service
Grafana
Prometheus
Elasticsearch
APM
OpsGenie
PagerDuty
Python
Bash
PowerShell
Observability
Metrics
Logs
Traces
Alerting
SLIs
SLOs
Error Budgets
Incident Command
Root Cause Analysis
Blameless Postmortems
Capacity Planning
AI Agents
Anomaly Detection
Chaos Engineering
Resilience Testing

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