Top Tech Jobs & Startup Jobs in Toronto

Build infrastructure and software for training, deploying, scaling, monitoring, and operating machine-learning models and optimization algorithms for supply-chain applications. Responsibilities include translating supply-chain use cases into mathematical models, developing ML and optimization systems in C++ and Python, designing automated testing strategies, and supporting cloud or containerized workloads. The role also involves research into heuristics, optimization, GPU computing, MLOps, and AI-assisted software development.

Develop full-stack enterprise application features using TypeScript, React, C#, and .NET, with emphasis on user experience, performance, scalability, and maintainability. Design and present technical solutions, build automated tests, prototype solutions, collaborate with engineering, product, and UX teams, and adopt emerging technologies including generative AI. The role also involves leading complex feature development, creating reliable APIs, and mentoring junior engineers.

Develop and maintain production scheduling algorithms for Kinaxis’s enterprise supply chain platform. Design computational and mathematical models, constraints, heuristics, and metaheuristics; apply optimization and selective AI/ML techniques; and deliver scalable, production-ready software. Responsibilities include testing, code reviews, defect triage, performance improvement, cross-functional collaboration, and support across the full software development lifecycle.

Leads enterprise application architecture across HR, Finance, Procurement, IT, Legal, Security, workplace, collaboration, and enterprise data platforms. Translates business strategy into secure, scalable solutions; defines architecture patterns, integrations, APIs, workflows, and data flows; evaluates technologies and AI capabilities; guides build-versus-buy decisions; leads architecture reviews; and mentors technical teams while influencing business and technology stakeholders.

Serves as the primary technical advisor for strategic enterprise customers, owning solution health, technical reviews, troubleshooting, root cause analysis, optimization, and customer initiatives. Partners with Customer Success, Support, Product Management, and Cloud Operations to improve adoption, stability, scalability, and retention. Requires deep Kinaxis Maestro expertise, enterprise SaaS experience, strong communication, and the ability to lead complex initiatives independently.

Lead applied AI and machine learning innovation for supply chain products. Develop prototypes and proof-of-concepts, evaluate emerging techniques, and guide promising ideas toward scalable enterprise capabilities. Provide technical leadership across research, product, and engineering teams while remaining hands-on with ML, generative AI, agents, LLMs, optimization, recommendation, and explainability. Influence architecture and technical direction, mentor colleagues, assess AI-generated code, and ensure solutions meet quality, security, maintainability, and customer-impact standards.

Leads enterprise cybersecurity risk management across cloud, product, third-party, and AI-enabled environments. Responsibilities include risk identification, assessment, prioritization, treatment planning, control evaluation, residual risk analysis, risk reporting, regulatory alignment, audit readiness, and risk register governance. The role supports FedRAMP, SOC 2, ISO 27001, and AI risk management initiatives while influencing engineering, product, legal, and compliance stakeholders and improving risk processes, metrics, tooling, and automation.

Develop and optimize supply-chain algorithms by translating real-world problems into mathematical models. Lead C++ implementation, investigate heuristics and optimization techniques, and create comprehensive functional, regression, performance, unit, and integration tests. Collaborate with agile teams and stakeholders while improving software quality, development speed, and platform capabilities. Experience with commercial mathematical solvers, data structures, algorithms, and AI-assisted development is valued.

Leads the architecture and hands-on evolution of Kinaxis Maestro’s cloud-native core platform. Designs distributed database, storage, query execution, and data-processing systems for massive scale, elasticity, performance, resilience, and cost efficiency. Guides architectural standards across Product R&D, prototypes and implements solutions, mentors senior engineers, and influences technical direction across teams. Requires deep expertise in distributed production systems, cloud platforms, concurrency, consistency, and high-performance backend development using Go, C++, or similar languages.

Owns the vision, strategy, roadmap, and outcomes for major Maestro platform capabilities. Leads customer discovery, platform architecture decisions, AI agent capabilities, data product integration, developer tooling, and enterprise adoption. Partners with engineering, data, cloud, and go-to-market teams to deliver scalable APIs, SDKs, services, and administration experiences. Requires 8+ years of product management experience, strong AI and modern data platform knowledge, technical fluency, and the ability to influence senior stakeholders.