Principal Solutions Architect – Expert Services

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the complete delivery of strategic customer programs, from initial discovery to production deployment and operational integration.

• Act as the primary technical authority across multiple simultaneous enterprise projects.

• Foster alignment among customer stakeholders, implementation partners, product teams, and engineering groups.

• Guarantee timely project delivery within the defined scope, ensuring alignment with customer business goals.

• Offer executive-level guidance on AI transformation, enterprise intelligence, and operational modernization efforts.

• Work alongside product, presales, and delivery teams to convert business use cases into knowledge graph-based architectures, reference implementations, and solution blueprints.

• Design scalable enterprise architectures utilizing Intelligence Center X, AI Studio, Mendix, Graph, and cloud-native technologies.

• Create enterprise knowledge graph solutions that link business processes, operational systems, products, data assets, and organizational knowledge.

• Develop graph-based semantic data models that facilitate enterprise intelligence, AI reasoning, contextual awareness, and relationship analytics.

• Implement architectural standards for security, governance, scalability, observability, and operational excellence.

• Lead the design and implementation of enterprise knowledge graphs using RapidMiner Graph Studio, showcasing expertise in conceptual modeling, ontology design, graph data management, query and inference techniques, and the engineering practices necessary for deploying and governing large-scale, production-grade knowledge graph systems.

• Establish best practices for performance, governance, scalability, and operational management.

• Assist customers in transforming isolated enterprise data into interconnected intelligence assets.

• Architect and implement agentic workflows to automate intricate business processes and decision-making tasks.

• Advise customers on identifying and prioritizing high-value AI use cases.

• Design enterprise intelligence solutions that integrate structured and unstructured data using knowledge graphs and AI services.

• Create governance models for AI agents, knowledge management, data access, and model utilization.

• Develop graph-powered retrieval and contextual reasoning architectures that enhance the effectiveness of enterprise AI agents.

• Promote the adoption of AI-driven automation while ensuring responsible, secure, and compliant implementation practices.

⛳️ Requirements

• A minimum of 12 years of experience in enterprise software delivery, solution architecture, consulting, or digital transformation leadership.

• At least 5 years of hands-on experience in designing and implementing graph database solutions and enterprise knowledge graphs.

• Extensive expertise in enterprise architecture, systems integration, cloud platforms, and distributed systems.

• Strong background in graph data modeling, ontology design, semantic architectures, and relationship analytics.

• Familiarity with competitive graph database technologies such as Neo4j, Amazon Neptune, TigerGraph, Stardog, ArangoDB, or similar platforms.

• Knowledge of graph query languages, preferably including SPARQL, Cypher, Gremlin, or equivalent technologies.

• Experience leading large-scale technology implementations for Fortune 1000 companies.

• A solid understanding of AI, machine learning, generative AI, agentic AI, and enterprise automation platforms.

• Experience with context engineering strategy: determining what information is loaded, how it is chunked, summarized, ordered, and governed across tools, skills, and knowledge sources.

• Proven success in managing executive stakeholder relationships and complex delivery programs.

• Outstanding communication, facilitation, leadership, and consulting skills.

• A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.

🏝️ Benefits

• Preferred qualifications include experience in manufacturing and Product Lifecycle Management (PLM), covering product structures, bills of materials (BOMs), engineering change management, and digital thread initiatives.

• Experience in implementing graph-based digital thread, product intelligence, or manufacturing knowledge graph solutions is advantageous.

• Familiarity with semantic web standards, RDF, OWL, linked data, and knowledge representation frameworks is a plus.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud is beneficial.

• Knowledge of implementing Retrieval-Augmented Generation (RAG), agent frameworks, and enterprise AI architectures is desirable.

• Understanding of enterprise data governance, master data management, and metadata management practices is important.

• An advanced degree in Computer Science, Engineering, Data Science, Information Systems, or a related field is preferred.

• Relevant certifications in cloud, architecture, AI, or graph technology are advantageous.