AI Engineer

Fulfillment IQ • Toronto, ON

8d • Hybrid

About The Position

Fulfillment IQ is a supply chain engineering and transformation company that helps brands, retailers, and 3PLs design, build, and scale high-performance logistics operations. We work at the intersection of strategy, operations, and technology where we solve complex, real-world problems across warehouse design, automation, order management, transportation, and end-to-end supply chain execution. Our teams combine deep domain expertise with strong technical capability, delivering outcomes through consulting, systems implementation, and proprietary platforms that accelerate time-to-value and reduce delivery risk. If you enjoy working in complex environments, partnering closely with clients, and seeing your work make a tangible impact on how global commerce moves, this is the place where your skills and judgment truly come to life. This is a high-impact, senior engineering role, where engineers are expected to operate with significant ownership and minimal oversight. The role focuses on building production-ready AI systems in an environment where speed, correctness, and architectural decisions have long-term implications. The ideal candidate is a seasoned AI engineer (ninja-level) with hands-on experience in developing and deploying real LLM systems, who excels in environments with significant ownership responsibilities and values impactful work more than structured, low-risk settings. Individuals driven by ownership, autonomy, and the opportunity to build from the ground up (rather than being a small cog in a large organization) will thrive here.

Requirements

• Strong backend/software engineering foundation (Python, APIs, system design)
• Proven experience shipping LLM-powered features to production
• Deep expertise in RAG systems (advanced retrieval + evaluation)
• Deep expertise in LLM evaluation methodologies (golden sets, regression testing)
• Deep expertise in Prompt engineering at API level
• Deep expertise in Agent architectures (ReAct, tool calling, planning loops)
• Strong understanding of trade-offs (cost, latency, scalability)
• Ability to work independently in ambiguous, fast-moving environments
• Bachelor's or master's degree in computer science or a related discipline
• Advanced Python and backend engineering
• LLM systems (RAG, agents, prompting, evaluation)
• API design and system architecture
• Docker, Git, CI/CD
• Understanding of inference systems and scaling
• High ownership and accountability
• Ability to operate in ambiguity (“build while flying”)
• Strong decision-making and trade-off analysis
• Clear communication with cross-functional teams

Nice To Haves

• Fine-tuning experience (LoRA, SFT, DPO)
• Inference stack experience (vLLM, TGI, llama.cpp)
• Observability tooling (Langfuse, LangSmith)
• Prior experience in early-stage or high-ownership teams
• Public work (GitHub, blogs, talks) demonstrating depth

Responsibilities

• Design and build production-grade LLM systems (RAG, agents, APIs)
• Architect systems that minimize rework in fast-evolving environments
• Own end-to-end delivery of critical AI features
• Define and implement evaluation frameworks
• Optimize systems for cost, latency, and reliability
• Collaborate across teams where needed
• Provide technical guidance where applicable (especially for less experienced engineers on adjacent teams)

Benefits

• Build systems that directly impact global commerce and supply chain performance.
• Investment in mentorship, leadership development, learning budgets, and long-term career growth.
• Support for remote and hybrid work models by offering multiple office locations.
• Recognition of impact, celebration of milestones, and reward for performance.
• Work alongside talented engineers, product leaders, and award-winning domain experts who value ownership, transparency, and high standards.
• Comprehensive health and dental coverage for you and your family.
• Competitive paid time off and flexible leave policies.
• Retirement savings programs and employer contributions.
• Dedicated learning and development budget.
• Remote and hybrid work options.
• Equipment allowances.
• Internet reimbursements.
• Business travel coverage.
• Employee stock options (ESOP), where applicable.
• Team events, meetups, and company offsites.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior