Senior AI Engineer

Job Title: Senior AI Engineer Company: Safe Fleet Job Category: Data Science Roles & Responsibilities: ABOUT THIS ROLE This is a builder and enabler role, not a research role. You will modernise our AI stack, create reusable AI services and agent infrastructure, automate critical operational workflows, and raise the AI capability of the engineers around you. Success is measured by what the rest of the team can build because of the foundation you put in place. You will also apply AI\-Native Engineering and Agentic SDLC practices to your own work — using AI coding agents, Spec\-Driven Development and automation to accelerate delivery while holding a high bar for quality, security and maintainability — and establish those practices as the team standard. From time to time you may contribute to customer\-facing AI capabilities in our product portfolio, but the centre of this role is internal platform, enablement and automation. RESPONSIBILITIES * Build the foundation other engineers build on — reusable AI services, agent scaffolding, shared libraries, prompt and context management, and integration patterns that let the team create agents without reinventing the groundwork. * Modernise and own SafeFleet’s AI stack: model selection and routing, provider abstraction, cost and token governance, and a clear upgrade path as the technology moves. * Design and implement RAG architectures, retrieval and indexing pipelines, and the data access patterns agents depend on. * Build Model Context Protocol (MCP) servers and tool integrations that expose internal systems safely to agents. * Establish AI evaluation, observability and guardrails — eval harnesses, regression testing for prompts and agents, tracing, quality and cost monitoring in production. * Develop robust backend services and APIs that make AI capability consumable across teams. * Automate critical operational workflows using AI — partnering with teams across Cloud Engineering to identify high\-toil processes and replace them with reliable, auditable agent\-driven automation. * Build agents and workflows that support areas such as diagnostics, triage, routine remediation, documentation and operational reporting. * Define governance for autonomous action: guardrails, human\-in\-the\-loop checkpoints, failure modes and auditability. Enablement and Technical Leadership * Mentor the engineering team on its AI journey — through pairing, workshops, documented patterns, internal guides and worked examples that move the whole group forward. * Set AI engineering standards: architecture patterns, prompt and agent design conventions, testing expectations, security and data\-handling practice. * Lead architecture and design discussions, review AI\-related work, and act as the technical reference point for AI across Cloud Engineering. * Apply AI\-Native Engineering throughout the development lifecycle, using AI coding agents, Spec\-Driven Development and automation to accelerate delivery. * Build custom AI coding agents, reusable agent skills and automated workflows for implementation, testing, verification, code review and release. * Integrate agent\-assisted verification into CI/CD, and continuously improve Agentic SDLC practice as a team\-wide standard. The final offer will be determined based on a combination of factors including skills, experience, and alignment with the role’s responsibilities.* Work Location: Coquitlam, BC, Canada Availability: Full time

Salary Range: $120,000 \- $135,000/yr * 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 Requirements: Key Skills: Data Science Salary: CAD 120000 - 135000 per yearly