Staff Supply Chain Simulation Engineer

Job Title: Staff Supply Chain Simulation Engineer

Primary Job Location: Toronto, ON, Canada

Location Flexibility: Hybrid, Toronto based

Employment Type (Permanent/Contract/Part-time/Intern): Permanent, Full-Time

Hiring Timeline (Hiring month): Immediate

Reporting Line: Chief Scientist

Existing Vacancy: Yes

Application Deadline: Open until filled

Base salary range: 145,00K - 170,00K CAD per year with a 12 percent target bonus.

About Fulfillment IQ (FIQ)

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, supply chain, 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.

Role Overview

Workbench is FIQ's warehouse-design platform: it lets a solutions engineer draw a warehouse the way an architect draws a building. You will design, build and own Workbench's warehouse simulation engine, wherein a warehouse design is simulated and evaluated against multiple operational scenarios. Reporting directly to the Chief Scientist, you will create simulation models that capture warehouse operations dynamics, design and build the engine that executes them, and lead its integration into our main product.

This is a unique opportunity to build something from scratch, assemble a team, and have a direct influence on product features and technical roadmap. You will work closely with our Chief Scientist, domain experts, and developers to build a capability that does not exit. It is a genuine zero-to-one build, and you will own the simulation vertical as it grows.

What You'll Do

• Translate warehouse operational processes into mathematical simulation models at various levels of granularity
• Identify the right simulation paradigm (or combination thereof) for the problem at hand and the best tools to solve it.
• Benchmark the performance of the simulation engine across various types of warehouse operations
• Drive the discussion around simulation as a product by prioritizing features, establishing a technical and product roadmap, and overseeing development and integration efforts
• Assemble and lead the team that will help build and maintain the simulation engine
• Lean on AI tools for execution and spend your judgment on the ambiguous parts.

The Honest Version of the Hard Parts

• This is genuinely zero-to-one. There is no reference tool to copy and no clean spec to build from, so the hardest part is the ambiguity. You will often start without a clear definition of what to build and will have to think your way through it.
• Your models will shape how real warehouses get designed. All models have limitations, so it is important to be honest about what they capture and what they don't
• You are the lead. You carry the open questions and the vertical, not just the modeling, and you will switch context fast as the product takes shape

Where This Goes

Think chessboard, not ladder. You will own and grow the simulation vertical, and there is real room to move into deeper research alongside the Chief Scientist and into a broader product and platform role. Tell us what you want to build and we will help you get there.

How We'll Interview You

• Intro conversation: a short call to swap context and make sure the basics line up
• Conversation with the Chief Scientist: a first call on how you think.
• Technical: a scripted, comparable working session on a real simulation problem. How you frame it, model it, handle missing information, and defend it.
• Final: discussion with the Workbench team

What You Need To Have

• Experience and understanding of warehouse or supply chain operations
• Hands-on experience in designing and building simulation models, with a good understanding of different simulation paradigms and when to use (or not to use) them
• Comfort in a zero-to-one, high-ambiguity environment, and the thinking to move forward when the problem is not yet defined
• Strong engineering ability to build the models and the tooling around them, with AI leaned on for the ex