Principal Solutions Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Solutions Architect - Expert Services based in United States.

• Lead end-to-end delivery of strategic enterprise programs, from discovery and solution design through implementation, production deployment, adoption, and value realization.
• Act as the primary senior technical leader across multiple complex customer engagements, coordinating customer stakeholders, partners, product teams, and engineering organizations.
• Provide executive-level guidance on enterprise AI transformation, intelligent automation, modernization, and emerging agentic enterprise strategies.
• Translate business objectives and use cases into scalable solution architectures, reference implementations, technical blueprints, and implementation plans.
• Design enterprise architectures leveraging agentic AI, knowledge graphs, AI services, application platforms, and cloud-native technologies while meeting security, governance, scalability, and observability requirements.
• Architect enterprise knowledge graph solutions connecting business processes, operational systems, products, data assets, and organizational knowledge.
• Lead the design and implementation of production-grade knowledge graphs, including conceptual models, ontology design, semantic data models, graph management, querying, inference, performance, and governance.
• Establish graph architecture best practices that enable disconnected enterprise data to become connected, contextual intelligence assets.
• Architect agentic workflows that automate complex business processes and support AI-driven decision-making.
• Help customers identify, prioritize, and implement high-value AI use cases while establishing responsible governance for agents, knowledge, data access, and model utilization.
• Design graph-powered retrieval and contextual reasoning architectures that improve the effectiveness and reliability of enterprise AI agents.
• Apply context engineering strategies covering information selection, chunking, summarization, ordering, and governance across tools, skills, and knowledge sources.
• Drive delivery quality, customer adoption, operational readiness, and measurable business outcomes throughout the engagement lifecycle.
• Develop reusable implementation assets, architectural frameworks, methodologies, and best practices while contributing insights to product strategy and continuous improvement.

• 12+ years of experience in enterprise software delivery, solution architecture, consulting, digital transformation, or technology 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, distributed systems, and scalable technology environments.
• Strong experience with graph data modeling, ontology design, semantic architectures, relationship analytics, and knowledge representation.
• Experience with graph database technologies such as Neo4j, Amazon Neptune, TigerGraph, Stardog, ArangoDB, or comparable platforms.
• Knowledge of graph query languages, ideally including SPARQL, Cypher, Gremlin, or equivalent technologies.
• Experience leading complex, large-scale technology implementations for Fortune 1000 or similarly sophisticated enterprise organizations.
• Strong understanding of artificial intelligence, machine learning, generative AI, agentic AI, and enterprise automation platforms.
• Demonstrated experience with context engineering strategies for managing information across AI tools, skills, and knowledge sources.
• Proven ability to manage executive stakeholder relationships and lead complex, multi-stakeholder delivery programs.
• Exceptional communication, facilitation, consulting, problem-solving, and leadership capabilities.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline.
• Preferred: Experience in manufacturing, Product Lifecycle Management (PLM), product structures, bills of materials, engineering change management, or digital thread initiatives.
• Preferred: Experience implementing graph-based digital thread, product intelligence, or manufacturing knowledge graph solutions.
• Preferred: Familiarity with RDF, OWL, linked data, semantic web standards, and knowledge representation frameworks.
• Preferred: Experience with AWS, Azure, Google Cloud, RAG architectures, agent frameworks, or enterprise AI implementations.
• Preferred: Knowledge of enterprise data governance, master data management, and metadata management practices.
• Preferred: Advanced degree or relevant certifications in cloud architecture, AI, enterprise architecture, or graph technologies.

• $150,000– (salary range incomplete in source)