Jobs at Kinaxis

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.

Provides financial analysis, forecasting, budgeting, modeling, reporting, and dashboard development for business units. Partners with stakeholders and HR to evaluate performance, explain KPI trends, support business cases, and guide strategic investment decisions. The role also improves reporting processes, presents financial insights to senior audiences, and mentors junior team members.

Design, build, test, and support enterprise software, APIs, automation workflows, and developer-facing platform capabilities. Develop secure, reliable, performant cloud-native solutions primarily on Azure and GCP. Contribute to architecture, engineering standards, testing, CI, and code reviews while collaborating across teams. Mentor colleagues through technical guidance and knowledge sharing, and help create self-service administration and developer productivity tools for the Maestro platform.

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.

Leads global FP&A strategy, including enterprise planning, budgeting, forecasting, financial modeling, scenario analysis, management reporting, KPI development, and executive and investor communications. Partners with senior leaders to guide investment, resource allocation, pricing, and growth decisions. Modernizes finance through automation, AI-enabled analytics, planning technologies, process improvement, and data governance. Builds and develops a high-performing global FP&A organization while driving finance transformation.

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.

Execute, optimize, and analyze multichannel B2B digital demand-generation campaigns across paid, organic, search, CRM, and programmatic channels. Manage campaign setup, targeting, tracking, governance, reporting, and agency coordination. Analyze metrics such as MQLs, MQAs, CPL, conversion efficiency, influenced pipeline, and ROI, translating findings into optimization recommendations and actionable business insights.

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.

Leads solution architecture for customer-facing platforms spanning CRM, support, partner engagement, revenue operations, and digital experiences. Translates business requirements into scalable, secure architectures; develops integration, data, API, workflow, and governance designs; evaluates emerging AI/ML capabilities; guides implementation decisions; and influences cross-functional stakeholders. The role also mentors architects, promotes reusable patterns, and aligns solutions with customer experience, revenue, security, compliance, and long-term business objectives.

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.