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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting large-scale graph, semantic, and data platforms, integrating structured and unstructured data across enterprise systems. Proficient in agentic AI, knowledge graph development, and defining reusable architecture patterns to drive innovation and technical direction.
Highest-signal resume keywords
Agentic AI DevelopmentKnowledge Graph ArchitectureData ModelingEnterprise Software ArchitectureSemantic Systems Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingSemantic ModelingKnowledge GraphIntegration ArchitectureEntity ResolutionSchema AlignmentIngestion PipelinesTransformation and MappingBatch UpdatesStreaming Updates
Soft Skills
Technical LeadershipMentoringCommunication
Tools & Technologies
SalesforceWarehouse Management SystemsRDFOWLSHACLSPARQLGitHub
Certifications & Qualifications
Masters in Computer SciencePhD in Artificial Intelligence
Industry Keywords
Enterprise SoftwareSupply Chain TechnologyOperational IntelligenceDigital TwinsAgentic Engineering
About the role
Key responsibilities & impact- Provide hands-on technical leadership in agentic AI, knowledge graph, semantic, and data modeling architecture
- Design platform-level tooling connecting Maestro and planning data with enterprise systems such as warehouse management, inventory, Salesforce, and partner agentic environments
- Design data, graph, and integration architecture, including ingestion pipelines, transformation and mapping, entity resolution, schema alignment, validation, batch updates, and streaming updates
- Develop patterns allowing agents to traverse enterprise data and graph structures
- Contribute to technical decisions across platform architecture, graph architecture, data modeling, AI integration, agentic workflows, quality evaluators, constraint validation, and query-time reasoning at scale
- Mentor others and help build a culture of structured thinking, semantic clarity, pragmatic platform architecture, agentic engineering, and product-oriented innovation
- Architect large-scale graph, semantic, and data platforms integrating structured, semi-structured, and unstructured data across enterprise systems
- Drive technical evaluation of emerging graph, semantic, agentic AI, and enterprise data technologies with defensible trade-off analysis
- Influence technical direction across product, engineering, platform, and customer-facing domains
- Define reusable architecture patterns, quality architecture, validation patterns, constraints, guardrails, and scalable platform capabilities
Requirements
What you’ll need- Masters or PhD in Computer Science, Artificial Intelligence, or a related field
- Relevant experience in enterprise software architecture, applied AI, data modeling, knowledge graph or semantic systems, or supply chain technology
- Deep practical understanding of enterprise supply chain systems or adjacent operational systems
- Strong hands-on experience designing platform-level software, developer tooling, composable capabilities, workbench-style products, prototypes, proof-of-concepts, or early systems
- Strong data modeling, semantic modeling, ontology, knowledge graph, or knowledge representation experience
- Experience defining reusable architecture patterns, data model governance, semantic or ontology standards, versioning, lifecycle management, and enterprise-domain alignment
- Ability to define long-term evolution strategies for agentic enterprise platforms
- Experience applying emerging techniques in agentic AI, knowledge representation, semantic systems, or enterprise data platforms
- Hands-on experience with knowledge graph, data, and integration platforms and pipelines
- Hands-on agentic AI and agentic engineering experience is required, including building software artifacts, applications, plans, evaluators, or workflows using agentic development approaches and GitHub-native engineering practices
- Demonstrated ability to identify, evaluate, and apply emerging research and technologies in agentic AI, knowledge representation, semantic systems, and enterprise platforms
- Strong technical judgment in evaluating semantic, graph, agentic AI, enterprise integration, and platform technologies
- Demonstrated ability to influence technical direction across product, engineering, platform, and customer-facing domains
- Excellent communication skills
- Ability to distinguish platform architecture from customer-specific implementation
- Ability to define quality architecture for agentic systems, including evaluators, validation patterns, constraints, and guardrails
- Experience with semantic technologies such as RDF, OWL, SHACL, or SPARQL is nice to have
- Background in temporal modeling, digital twins, operational intelligence systems, or enterprise orchestration platforms is nice to have
- Experience contributing to research, standards, open-source projects, or innovation is nice to have
- Experience with enterprise SaaS products and operating AI, graph, data, or agentic platforms at scale is nice to have
- Experience with RAG, LLM applications, explainable AI, evaluators, or agentic quality frameworks is nice to have
Benefits
Comp & perks- Flexible vacation and Kinaxis Days (company-wide days off)
- Flexible work options
- Physical and mental well-being programs
- Regularly scheduled virtual fitness classes
- Mentorship programs, training, and career development
- Recognition programs and referral rewards
- Hackathons
- Accommodations upon request to ensure fairness and accessibility throughout the recruitment process