Principal Solutions Architect

About the role

This senior technical position guides enterprise customers through implementing and optimizing Intelligence Center X, an agentic AI platform. You will lead solution architecture across complex engagements, translating business goals into scalable systems that connect people, processes, products, and data through graph-powered intelligence and AI automation. The role spans the full delivery lifecycle from discovery through production deployment and value realization.

Key facts

What you'll do

• Direct end-to-end delivery of strategic customer programs from initial discovery through production deployment and ongoing operations
• Act as primary technical leader across multiple simultaneous enterprise engagements
• Design enterprise architectures using Intelligence Center X, AI Studio, Mendix, Graph, and cloud-native technologies
• Build enterprise knowledge graph solutions connecting business processes, operational systems, products, data assets, and organizational knowledge
• Create graph-based semantic data models supporting AI reasoning, contextual awareness, and relationship analytics
• Lead design and implementation of enterprise knowledge graphs using RapidMiner Graph Studio, covering conceptual modeling, ontology design, graph data management, and query techniques
• Architect agentic workflows that automate complex business processes and decision-making activities
• Help customers identify and prioritize high-value AI use cases
• Establish governance models for AI agents, knowledge management, data access, and model utilization
• Provide executive-level guidance on AI transformation and operational modernization initiatives
• Coordinate alignment across customer stakeholders, implementation partners, product teams, and engineering organizations

Requirements

• 12+ years in enterprise software delivery, solution architecture, consulting, or digital transformation leadership
• 5+ years hands-on experience designing and implementing graph database solutions and enterprise knowledge graphs
• Deep knowledge of enterprise architecture, systems integration, cloud platforms, and distributed systems
• Strong background in graph data modeling, ontology design, semantic architectures, and relationship analytics
• Experience with graph database technologies such as Neo4j, Amazon Neptune, TigerGraph, Stardog, ArangoDB, or comparable platforms
• Familiarity with graph query languages including SPARQL, Cypher, Gremlin, or equivalent
• Track record leading large-scale technology implementations for Fortune 1000 organizations
• Solid understanding of AI, machine learning, generative AI, agentic AI, and enterprise automation platforms
• Experience with context engineering strategy covering information loading, chunking, summarization, ordering, and governance across tools, skills, and knowledge sources
• Proven success managing executive stakeholder relationships and complex delivery programs
• Strong communication, facilitation, leadership, and consulting abilities
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Nice to have

• Background in manufacturing and Product Lifecycle Management including product structures, bills of materials, engineering change management, and digital thread initiatives
• Experience implementing graph-based digital thread, product intelligence, or manufacturing knowledge graph solutions
• Knowledge of semantic web standards, RDF, OWL, linked data, and knowledge representation frameworks
• Experience with AWS, Azure, or Google Cloud platforms
• Experience implementing Retrieval-Augmented Generation, agent frameworks, and enterprise AI architectures
• Understanding of enterprise data governance, master data management, and metadata management practices
• Advanced degree in Computer Science, Engineering, Data Science, Information Systems, or related field
• Relevant cloud, architecture, AI, or graph technology certifications

Skills & tools

• Intelligence Center X
• AI Studio
• Mendix platform
• RapidMiner Graph Studio
• Graph databases: Neo4j, Amazon Neptune, TigerGraph, Stardog, ArangoDB
• Graph query languages: SPARQL, Cypher, Gremlin
• Enterprise knowledge graph architectures
• Semantic data modeling and ontology design
• Agentic AI and enterprise automation
• Cloud-native technologies
• RAG architectures and agent frameworks

Practical notes

• Mendix is a Siemens business, acquired in 2018
• Siemens is an Equal Opportunity and Affirmative Action Employer
• California residents receive additional privacy notices regarding personal information