AI Solutions Architect

About Neo4j: Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community. Intelligence that works. Results that matter. Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business. Our Vision: At Neo4j, we have always strived to help the world make sense of data. As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive. Key Responsibilities Solution Architecting: Partner with customer technical leads, customer executives, and partners to manage and deliver successful implementations of Graph+GenAI solutions becoming a trusted advisor to decision-makers throughout the engagement. Propose solution architectures and manage the deployment of Graph+GenAI solutions according to complex customer requirements and implementation best practices. Engage directly with customers to understand their business objectives and translate them into AI-powered solutions that leverage graph databases and LLMs. This includes gathering requirements, understanding existing data landscapes, and identifying opportunities to apply graph-based AI to solve business challenges. Interact with customer stakeholders to manage project scope, priorities, deliverables, risks and issues, and timelines for successful customer outcomes. Solution Engineering Develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks. This involves writing production-level code, optimising for performance and scalability, and ensuring seamless integration with customer systems. Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications, incorporating new techniques and technologies as they emerge. Education & Enablement Collaborate with other teams at Neo4j (Product and Marketing) to influence the roadmap and provide insights from the field, and package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets. Share your expertise internally with other Neo4j teams and also with customers through workshops, training sessions, and documentation to empower them to effectively utilise, maintain, and reproduce the AI solutions you deliver. Maintain continuous learning and stay up-to-date with the rapidly evolving GenAI landscape, proactively seeking knowledge of new trends and technologies. Required Qualifications Enterprise Application Development: 5+ years of experience in designing and developing enterprise-class applications, demonstrating a strong understanding of software development lifecycle principles. LLM Proficiency: 2+ years of Experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and integrating LLMs into applications. Maintain up-to-date knowledge of different LLM providers and their strengths and limitations (e.g., OpenAI’s GPT and O families, Anthropic’s Claude family, Google’s Gemini, xAI’s Grok, as well as open-source LLMs like LLama, DeepSeek, and Mistral). Programming Proficiency: Competence and hands-on experience in at least one of the following languages: Java, JavaScript, Python, or C#. Ability to write clean, maintainabl