Manager, Solver Infrastructure

Location

Ottawa and Toronto, Canada - Hybrid

Other Canadian locations - Remote

About the role

Kinaxis is looking for a Manager, Solver Infrastructure to lead the team responsible for the technology and infrastructure behind large- scale mathematical optimization in Maestro.

This is a hands-on technical leadership role at the intersection of Operations Research, software engineering, cloud infrastructure, and high-performance computing. You will lead a team focused on making optimization faster, more scalable, and more reliable, while helping bring emerging solver and AI technologies into production.

Vacancy Status

This is an existing job vacancy

What you will do

• Lead, mentor, and grow a team of engineers, creating an environment of strong technical execution, collaboration, and continuous development.
• Set clear expectations, provide regular feedback and coaching, and support the performance and career development of team members.
• Provide hands-on technical leadership across solver integration, architecture, performance, scalability, and production reliability.
• Evolve the platform supporting mathematical optimization, including solver interfaces, distributed execution, deployment, monitoring, and diagnostics.
• Drive solve acceleration through GPU computing, advanced solver technologies, improved hardware utilization, and AI/ML approaches.
• Improve the reliability, observability, and operational readiness of optimization workloads across cloud environments.
• Collaborate closely with Operations Research, Product, Architecture, Cloud Services, and technology partners to turn new ideas into production capabilities.

What we are looking for

• 5+ years of experience in software engineering, platform engineering, or applied optimization, including 2+ years leading teams.
• Strong technical background in Operations Research, software engineering, optimization systems, or related computational technologies.
• Experience with mathematical optimization and commercial solvers such as Gurobi, CPLEX, or Xpress.
• Strong software engineering fundamentals, ideally with C++ and/or Python experience.
• Experience building or operating cloud-based and distributed systems, including technologies such as Kubernetes and containers.
• A strong problem-solving mindset and the ability to investigate complex performance and reliability challenges across software and infrastructure.
• Strong communication and collaboration skills, with the ability to make complex technical topics accessible to different audiences.
• Bachelor's or Master's degree in Computer Science, Operations Research, Industrial Engineering, Engineering, Applied Mathematics, or a related field.
• Nice to have:
  • Experience with GPU computing or GPU-accelerated optimization.
  • Experience with Gurobi Compute Server or similar distributed solver infrastructure.
  • Experience applying AI/ML to optimization, solver acceleration, tuning, or explainability.
  • Experience with high-performance computing or distributed optimization.
  • Knowledge of supply chain planning and large-scale enterprise optimization.

#Senior; #LI-EM1