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Architect, Operations Research

Remote / Online - Candidates ideally in
Québec, Province de Québec, Canada
Listing for: Kinaxis
Remote/Work from Home position
Listed on 2026-05-14
Job specializations:
  • Engineering
    AI Engineer (Applied/Software)
  • IT/Tech
    Data Scientist, AI Engineer (Applied/Software)
Job Description & How to Apply Below
About Kinaxis
Elevate your career journey by embracing a new challenge with Kinaxis. We are experts in tech, but it’s really our people who give us passion to always seek ways to do things better. As such, we’re serious about your career growth and professional development, because People matter at Kinaxis.

In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, with a brand-new HQ based in Kanata North in Ottawa. As one of Canada’s Top Employers, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.

At Kinaxis, we power the world’s supply chains to help preserve the planet’s resources and enrich the human experience. As a global leader in end-to-end supply chain management, we enable supply chain excellence for all industries, with more than 40,000 users in over 100 countries. We are expanding our team as we continue to innovate and revolutionize how we support our customers.

Location

This is a remote position. You can work from home and be located anywhere in Canada

About

The Role
The Operations Research Architect drives the next generation of optimization and algorithmic capabilities within our platform. As part of the Product R&D team, you will lead the development of large-scale mathematical models and high-performance algorithms that solve some of the most complex supply chain problems in the world.

Vacancy Status

This is an existing job vacancy

What you will do
As Operations Research Architect you will define and drive the optimization and algorithmic strategy behind large-scale supply chain systems, shaping how advanced techniques, including mathematical optimization, heuristics, and hybrid ML/OR approaches, are designed, implemented, and evolved.

You will guide the development of high-performance models that operate on massive datasets and deliver results in seconds.

You will operate as a technical authority across Product R&D, setting direction for modeling approaches, solver strategies, and algorithm design. You will mentor senior engineers and researchers, elevate the organization’s approach to optimization and performance, and foster a culture grounded in analytical rigor and engineering excellence.

What we are looking for
All aspects of the operations research lifecycle are second nature to you—from problem formulation and mathematical modeling to algorithm design, optimization, and large-scale execution. You are passionate about solving complex, real-world problems, and you know how to balance mathematical rigor and practical performance at scale.

You are deeply experienced in translating complex supply chain challenges into well-structured optimization models and algorithms, and you think naturally in terms of constraints, trade-offs, and objective functions. You continuously push for better formulations, faster solvers, and more impactful solutions that drive measurable outcomes.

You are a strong collaborator and communicator, comfortable working with product managers, engineers, and domain experts. You bring clarity to highly complex problems, frame them mathematically, and guide teams toward solutions that balance optimality, scalability, and real-world constraints.

PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related field.

Extensive experience designing and delivering optimization models and algorithms in production environments.

Experience in supply chain management, logistics, or large-scale planning systems.

Deep expertise in mathematical optimization techniques, including linear programming, mixed-integer programming, heuristics, and meta heuristics.

Proven ability to formulate and solve large-scale, real-world optimization problems, particularly in supply chain or related domains.

Strong experience with commercial solvers (e.g., Gurobi, CPLEX, Xpress) and performance tuning of optimization models.

Solid understanding of algorithm design, computational complexity, and numerical performance.

Proficiency in C++ or similar high-performance programming languages, with strong…
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