Ingénieur(e) principal(e) en systèmes d’IA | Senior AI Systems Engineer at MATADOR.IA INC. — NeverHard

About this position At Matador , we’re transforming how the automotive world connects and operates. We build cutting‑edge AI solutions that power real businesses and shape the future of the automotive industry. If you thrive at the intersection of robust backend systems and practical AI applications, you’ll feel right at home with us in the Greater Montreal area. Who We’re Looking For This isn’t theoretical work — you’ll design, build, and scale AI‑powered products that thousands of businesses rely on every day. You’ll move fast, tackle complex problems, and push the boundaries of what’s possible with multi‑agent, multimodal AI systems — and every change you ship will be backed by rigorous evals, not vibes. What You’ll Do Design and build multi‑agent LLM systems that coordinate tools, memory, and structured outputs — including agents that retrieve, reason over, and act on data from multiple sources (CRM, inventory, conversations). Drive eval‑driven development: build eval suites (offline benchmarks, LLM‑as‑judge, regression gates) and the observability and tracing needed to ship prompt and model changes with confidence. Build and integrate Model Context Protocol (MCP) servers and tools that connect agents to real business systems. Build realtime voice agents (speech‑to‑speech models, telephony integration) alongside text‑based messaging agents. Deploy AI workflows into scalable cloud infrastructure (AWS, MongoDB, etc.). Optimize model routing, cost, and latency across multiple model providers. What Makes You a Great Fit 3+ years of production‑grade software engineering experience (backend focus preferred). Solid experience with MongoDB (or comparable databases), AWS, and modern cloud architecture. An eval‑driven mindset: you measure AI changes against real‑world data before shipping them. Hands‑on experience with at least one of: Built LLM agents that coordinate multiple model calls and tools. Built eval pipelines (LLM‑as‑judge, regression gates) for LLM outputs on real‑world datasets. Built agentic retrieval systems (hybrid search, reranking, retrieval that feeds agent context). Bonus Points Experience with the Model Context Protocol (MCP), agent SDKs (Claude Agent SDK, OpenAI Agents SDK, LangGraph), or custom agent harnesses. Deep knowledge of context engineering, structured outputs, and tool orchestration with LLMs. Experience with AI guardrails: prompt‑injection resistance and PII handling in customer‑facing systems. You’ve shipped a real product and improved it through user feedback. Impactful work: Build AI products used by real businesses, not just experiments. Fast innovation: Ship quickly, learn fast, and stay ahead of the curve. Flexible work: Hybrid from our Laval office (Greater Montreal), with a collaborative, diverse team. Shape the industry: Bring AI’s best ideas to one of the world’s most dynamic sectors. Compensation: Competitive salary, group insurance, wellness benefit, retirement savings, and shuttle service from Côte‑Vertu and Montmorency metro stations. $110,000–$130,000 per year, based on experience. #J-18808-Ljbffr