Teams at Kinaxis

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.

Support production cloud systems and maintain service availability across Azure, GCP, AWS, and datacenter environments. Build infrastructure-as-code, CI/CD pipelines, deployment automation, and operational tooling using Terraform, GitHub Actions, ArgoCD, scripting, and Ansible. Manage production and lab environments, participate in on-call incident response, troubleshoot infrastructure and application issues, and collaborate with Product, Platform, Security, and Support teams to improve reliability and operational efficiency.

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.