Jobs at Kinaxis

Designs, implements, and operates security controls across corporate IT and SaaS environments spanning cloud and on-premises infrastructure. Leads cloud, platform, application, vulnerability-management, detection, and incident-response initiatives. Partners with engineering and operations teams to embed security into architectures, CI/CD pipelines, and infrastructure-as-code workflows; drives risk-based remediation and improves control effectiveness. Serves as a technical escalation point during complex incidents and mentors junior team members.

Leads the transformation of Product operations through AI, automation, integrated tooling, and redesigned workflows. Identifies high-value opportunities, builds scalable agents and automations, establishes secure operating practices, and measures improvements in velocity, capacity, quality, adoption, and decision-making. Partners with Product, IT, Security, Data, Legal, and R&D while driving AI fluency, reusable patterns, and enterprise-ready capabilities.

Partners with North American sales teams to improve forecasting, pipeline management, territory planning, and revenue performance. The role analyzes pipeline health, conversion rates, productivity metrics, and funnel performance; supports business reviews and forecast discussions; ensures CRM data quality and sales process compliance; and provides actionable insights to sales leadership. It also collaborates with Marketing, Analytics, and Operations on pipeline generation, process improvements, system enhancements, and operational priorities.

Provides technical leadership for cloud platform engineering, including cloud architecture, infrastructure automation, CI/CD, security, reliability, self-service delivery, and developer enablement. The role leads design and code reviews, mentors engineers, improves cloud services and delivery processes, and guides implementation across teams using public cloud platforms, Terraform, Kubernetes, and modern DevOps tooling.

Build production AI harness systems for Kinaxis’s Databricks-based enterprise Data Fabric. Responsibilities include developing agent execution frameworks, integrating LLMs with governed data, implementing tool calling and workflow controls, enforcing multi-tenant isolation, and delivering APIs, SDKs, libraries, templates, and operational runbooks. The role requires distributed-systems engineering, cloud data-platform experience, secure multi-tenant design, and practical expertise in agent orchestration, retrieval, evaluation, guardrails, metadata, lineage, and governance.

Conduct applied AI/ML research focused on time-series forecasting and generative AI for supply chain planning. Review literature, formulate hypotheses, design reproducible experiments, develop and evaluate models, analyze results, and communicate findings. Build research prototypes and collaborate with researchers, engineers, data scientists, and domain experts to assess product potential. Contribute to technical reports, demonstrations, publications, and patents under mentorship.

Leads strategic relationships with major global enterprise customers, driving business transformation, adoption, retention, and expansion. Develops account governance and joint strategies, coordinates cross-functional teams, engages executive stakeholders, identifies sales opportunities, influences roadmap alignment, tracks business value, manages escalations, and supports net revenue retention. Requires deep supply chain expertise, SaaS experience, Salesforce and Gainsight proficiency, and willingness to travel globally up to 20%.

Leads Kinaxis’s Advanced Mathematical Modelling function, managing architects, algorithm developers, and operations research specialists. Provides technical and strategic leadership across optimization, machine learning, simulation, decision science, and algorithm development. Partners with Product Management, Engineering, and customer teams to solve supply chain challenges, guides research and prototyping, shapes platform architecture, and promotes scalable production solutions. Oversees talent acquisition, coaching, workforce planning, performance management, and career development while establishing the function’s vision and operating model.

Leads enterprise integration architecture connecting Kinaxis Maestro with SAP, ERP systems, applications, and data sources. Defines integration strategies, patterns, data models, APIs, middleware, ETL, event-driven architectures, and technical designs. Advises customers, prospects, solution architects, engineering, and product teams; guides complex deployments, transformation programs, escalations, and innovation initiatives. Establishes reusable frameworks and standards, influences product direction, and mentors technical teams.

Lead global financial accounting, controllership, external reporting, internal controls, audit oversight, regulatory compliance, and revenue accounting for a public company. Partner with the CFO and Audit Committee on financial governance, risk management, reporting, and compliance. Oversee IFRS and US GAAP reporting, SEC and OSC filings, SOX and ICFR programs, audit readiness, and scalable accounting operations while developing high-performing teams.

Leads supply chain product innovation for high-tech and semiconductor customers. Responsibilities include solution design, process flows, user stories, test scripts, data flows, customer engagement, product feedback, consultant leadership, stakeholder coordination, and early-innovator deployments. The role supports product launches from strategic planning through growth, drives proof-of-value deliveries, and ensures scalable, supportable product capabilities while partnering with product management, engineering, professional services, and customers.

Design and develop technical learning content for Kinaxis supply chain software, including e-learning, instructor-led training, virtual training, hands-on labs, assessments, and performance-support materials. Analyze learner needs, apply instructional design and adult learning principles, collaborate with subject matter experts, validate technical content, manage curriculum projects, and maintain documentation. The role requires quickly learning complex enterprise products and delivering accessible, outcome-focused training across global audiences.

Own the demand planning product roadmap, translating customer and market needs into forecasting, demand sensing, scenario planning, and AI-enabled capabilities. Lead discovery, prioritization, and delivery with Engineering, Data Science, UX, and go-to-market teams. Define success metrics, monitor performance, represent customer needs, and drive cross-functional alignment. The role requires deep demand planning expertise, enterprise software product management experience, strong analytical and communication skills, and up to 20% travel.

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 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.

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.