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Principal Solution Architect - Graph 

Position Summary

As a Principal Solution Architect and Technical Lead, you serve as the senior technical advisor responsible for guiding enterprise customers through the successful implementation, adoption, and optimization of Intelligence Center X, an agentic AI platform. Partnering closely with customer executives, program stakeholders, and business audiences, you lead the delivery of transformative AI-powered solutions that drive measurable business outcomes.

In this role, you oversee solution architecture and implementation across complex enterprise engagements. You translate business objectives into scalable, secure, and integrated solutions leveraging Intelligence Center X, AI Studio, Mendix, Graph, and enterprise knowledge graph technologies while ensuring alignment with enterprise architecture standards, operational requirements, and organizational change initiatives.

The ideal candidate possesses deep expertise in graph databases, knowledge graph architectures, semantic data modeling, enterprise integration, and agentic AI. You will help customers build intelligent enterprises by connecting people, processes, products, systems, and data through graph-powered enterprise intelligence and AI-driven automation.

You provide leadership throughout the delivery lifecycle, including discovery, solution design, implementation oversight, adoption planning, and value realization. Acting as a trusted advisor to customer leadership, you help organizations modernize operations through agentic workflows, enterprise intelligence, digital thread initiatives, and AI-powered automation.

Success is measured by customer outcomes, platform adoption, delivery excellence, and the ability to establish Intelligence Center X as a strategic capability within the emerging agentic enterprise.

Key Responsibilities

Delivery Leadership

• Lead end-to-end delivery of strategic customer programs from discovery through production deployment and operationalization.

• Serve as the primary technical leader across multiple concurrent enterprise engagements.

• Drive alignment across customer stakeholders, implementation partners, product teams, and engineering organizations.

• Ensure projects are delivered on time, within scope, and aligned with customer business objectives.

• Provide executive-level guidance on AI transformation, enterprise intelligence, and operational modernization initiatives.

Solution Architecture

• Collaborate with product, presales, and delivery teams to translate business use cases into knowledge graph-based architectures, reference implementations, and solution blueprints.

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

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

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

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

Graph Databases and Enterprise Knowledge Graphs

• Lead the design and implementation of enterprise knowledge graphs using RapidMiner Graph Studio demonstrating expertise in conceptual modeling, ontology design, graph data management, query and inference techniques, and the engineering practices required to deploy and govern large-scale, production grade knowledge graph systems.

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

• Enable customers to transform disconnected enterprise data into connected intelligence assets.

Agentic AI and Enterprise Intelligence

• Architect and implement agentic workflows that automate complex business processes and decision-making activities.

• Guide customers in identifying and prioritizing high-value AI use cases.

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

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

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

• Drive adoption of AI-powered automation while ensuring responsible, secure, and compliant implementation practices.

Required Qualifications

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

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

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

• Strong experience with graph data modeling, ontology design, semantic architectures, and relationship analytics.

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

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

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

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

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

• Demonstrated success managing executive stakeholder relationships and complex delivery programs.

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

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

Preferred Qualifications

• Experience in manufacturing and Product Lifecycle Management (PLM), including product structures, bills of materials (BOMs), engineering change management, and digital thread initiatives.

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

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

• Experience with cloud platforms including AWS, Azure, or Google Cloud.

• Experience implementing Retrieval-Augmented Generation (RAG), agent frameworks, and enterprise AI architectures.

• Knowledge of enterprise data governance, master data management, and metadata management practices.

• Advanced degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.

• Relevant cloud, architecture, AI, or graph technology certifications.

• Experience in ADT sector.

Success Metrics

• Successful delivery of strategic enterprise programs and customer transformation initiatives.

• Customer adoption and expansion of Intelligence Center X and related platform capabilities.

• Measurable business outcomes achieved through AI, automation, and enterprise intelligence solutions.

• Successful deployment and operationalization of enterprise knowledge graph capabilities.

• Executive stakeholder satisfaction and customer advocacy.

• Development of reusable implementation assets, architectural frameworks, and best practices.

• Contribution to platform innovation, product strategy, and continuous improvement.

Closing

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.