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
