AI Engineer

Location Toronto, ON - Hybrid

Salary CAD $200,000 per year (negotiable)

Job type Full-time, Permanent

DATAHEAD is exclusively representing a senior AI Engineer position at a global supply chain tech firm trusted by Fortune 50 brands.

This is a high-ownership, senior engineering role focused on building production-grade AI systems - not maintaining someone else's pipeline. You'll be architecting and shipping LLM systems that directly impact how global logistics operates, reporting into the Head of R&D with real autonomy from day one.

If you thrive in environments where decisions matter, ambiguity is normal, and ownership is genuine -read on.

What you'll be doing

Design and build production-grade LLM systems — RAG pipelines, agents, and APIs
Own end-to-end delivery of critical AI features
Define and implement evaluation frameworks (golden sets, regression testing)
Architect systems for cost, latency, and reliability at scale
Drive architectural decisions with long-term implications
Provide technical guidance to engineers on adjacent teams

What you must have

Proven experience shipping LLM-powered features to production — this is a hard requirement
Deep expertise in RAG systems: advanced retrieval, chunking strategy, and evaluation
Strong backend engineering foundation — Python, API design, system architecture
Hands-on prompt engineering at API level, not just wrapper libraries
Experience with agent architectures: ReAct, tool calling, planning loops
Ability to operate independently in fast-moving, ambiguous environments
Bachelor's or Master's degree in Computer Science or a related field

Bonus if you have

Fine-tuning experience — LoRA, SFT, DPO
Inference stack experience — vLLM, TGI, llama.cpp
Observability tooling — Langfuse, LangSmith
Public work (GitHub, writing, conference talks) that demonstrates genuine depth
Prior experience on early-stage or high-ownership teams

What the first 90 days look like:

Month 1 — Get deep into the existing architecture. Contribute to live systems, not just onboarding tasks. Identify gaps and risks early.

Month 2 — Own and deliver a critical feature or system component end-to-end. Improve at least one existing system across performance, evals, or architecture.

Month 3 — Trusted senior engineer on the team. Driving architectural decisions. Delivering measurable impact on reliability, quality, or efficiency. Operating with minimal oversight.

Why this role

Real ownership — not a supporting role in a large org
Small, high-calibre team with deep operational domain expertise
Systems that directly power real-world global commerce
Competitive salary with room to negotiate
Hybrid working from Toronto
Full benefits, learning budget, flexible leave, and ESOP where applicable

DATAHEAD

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