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Kinaxis dezvoltă software pentru orchestrarea lanțurilor de aprovizionare, care ajută organizațiile să planifice, să gestioneze și să răspundă operațiunilor complexe. Platforma Maestro combină planificarea bazată pe inteligență artificială, analizele avansate și vizibilitatea datelor în timp real pentru a sprijini decizii mai bine fundamentate de-a lungul lanțului de aprovizionare. Soluțiile companiei sunt relevante pentru organizații din domenii precum producția, sănătatea și consultanța, punând accent pe îmbunătățirea eficienței, anticiparea cererii și adaptarea rapidă atunci când apar perturbări.
AI/ML and Agentic Systems Architect
Lead architecture for agentic AI, semantic, and knowledge-graph platforms supporting Kinaxis supply-chain orchestration software. Connect planning data with enterprise systems while building reusable AI capabilities at scale.
Descriere
- Lead hands-on architecture for agentic AI, knowledge graphs, semantic systems, and data modeling
- Create platform tooling that connects Maestro and planning data with warehouse management, inventory, Salesforce, and partner agentic environments
- Design data, graph, and integration architectures covering ingestion, transformation, mapping, entity resolution, schema alignment, validation, and batch or streaming updates
- Enable agents to navigate enterprise data and graph structures
- Shape technical decisions spanning platform and graph architecture, data modeling, AI integration, agentic workflows, quality evaluators, constraint validation, and query-time reasoning at scale
- Establish reusable architecture patterns and scalable platform capabilities
- Assess emerging graph, semantic, agentic AI, and enterprise data technologies through clear trade-off analysis
- Turn emerging research and technologies into scalable architecture patterns and product capabilities
- Mentor colleagues and foster structured thinking, semantic clarity, pragmatic platform architecture, agentic engineering, and product-focused innovation
- Partner across product, engineering, platform, and customer-facing teams
Cerințe
- Master’s or PhD in computer science, artificial intelligence, or a related discipline
- Relevant experience in enterprise software architecture, applied AI, data modeling, knowledge graphs, semantic systems, or supply chain technology
- Strong practical understanding of enterprise supply chain or related operational systems
- Hands-on experience designing platform software, developer tooling, composable capabilities, workbench products, prototypes, proof-of-concepts, or early-stage systems
- Strong background in data modeling, semantic modeling, ontologies, knowledge graphs, or knowledge representation
- Experience establishing reusable architecture patterns, data-model governance, semantic or ontology standards, versioning, lifecycle management, and cross-domain alignment
- Ability to plan the long-term evolution of agentic enterprise platforms
- Experience applying emerging methods in agentic AI, knowledge representation, semantic systems, or enterprise data platforms
- Experience architecting large-scale graph, semantic, and data platforms that combine structured, semi-structured, and unstructured data
- Hands-on experience with knowledge graph, data, and integration platforms and pipelines
- Experience with ingestion, transformation, entity resolution, schema or ontology alignment, validation, update strategies, and large-scale performance
- Required hands-on experience with agentic AI and agentic engineering
- Experience with GitHub-native engineering practices
- Ability to identify, assess, and apply emerging research and technologies
- Strong technical judgment
- Ability to influence technical direction across product, engineering, platform, and customer-facing groups
- Excellent communication skills
- Ability to separate platform architecture from customer-specific implementation
- Ability to define quality architecture for agentic systems, including evaluators, validation patterns, constraints, and guardrails
- Nice to have: experience with RDF, OWL, SHACL, or SPARQL
- Nice to have: experience with temporal modeling, digital twins, operational intelligence, or enterprise orchestration platforms
- Nice to have: experience in research, standards, open-source projects, or innovation
- Nice to have: experience with enterprise SaaS and operating AI, graph, data, or agentic platforms at scale
- Nice to have: experience with RAG, LLM applications, explainable AI, evaluators, or agentic quality frameworks
Beneficii
- Flexible vacation plus Kinaxis Days, including company-wide days off
- Flexible working arrangements
- Programs supporting physical and mental well-being
- Regular virtual fitness classes
- Mentorship, training, and career development programs
- Recognition programs and referral rewards
- Hackathon opportunities
- Recruitment accommodations available on request to support fairness and accessibility
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