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.
This senior-level role serves as a technical leader for complex enterprise AI transformation programs, guiding customers from discovery through production and operationalization.
You will architect scalable solutions that combine agentic AI, enterprise knowledge graphs, semantic data, applications, and cloud technologies.
The role requires deep expertise in graph architectures and the ability to translate ambitious business goals into practical technical solutions.
You will work directly with executives, technical teams, implementation partners, product organizations, and engineering stakeholders.
Your work will help organizations turn disconnected enterprise data into intelligent, contextual systems capable of supporting automation and decision-making.
You will also establish architecture, governance, security, and operational practices that enable responsible enterprise AI adoption.
Success will be measured through customer outcomes, platform adoption, delivery excellence, and the creation of reusable technical frameworks and best practices.
Accountabilities:
- 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.
Requirements:
- 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.
Benefits:
- $150,000–$250,000 annual OTE (on-target earnings).
- 100% remote work opportunity within the United States.
- Opportunity to lead high-impact enterprise AI and digital transformation initiatives.
- Exposure to advanced technologies spanning agentic AI, knowledge graphs, semantic data, cloud platforms, and enterprise automation.
- Direct engagement with senior executives and major enterprise organizations.
- Opportunity to shape reusable architecture frameworks, implementation methodologies, and technical best practices.
- Professional growth through work at the intersection of enterprise architecture, AI, graph technology, and intelligent automation.
- Opportunity to contribute to platform innovation, customer transformation, and strategic technology initiatives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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