Senior AI Solutions Architect

As a Senior AI Solutions Architect, you will lead the design, construction, and deployment of AI solutions that combine the power of graph databases and AI. You will act as a trusted advisor to our strategic customers, guiding them through complex data challenges and delivering transformative business value. You will have a great understanding of graph technologies, LLMs, and AI frameworks, and will be able to translate customer needs into production-ready AI applications grounded in real-world context using Neo4j Knowledge Graphs.

Responsibilities

Engage with technical leaders, stakeholders, and strategic partners to shape and guide successful implementation of Graph+GenAI solutions; design and advocate for robust, scalable solution architectures; collaborate closely with customer leadership to understand strategic objectives and translate them into high-impact AI solutions; lead stakeholder engagement across all levels to steer project scope, align priorities, mitigate risks, and ensure timely delivery; develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks; write production-level code, optimize for performance and scalability, and ensure seamless integration with customer systems; continuously evaluate and improve performance, scalability, and efficiency of deployed AI applications; work with Product and Marketing to influence roadmap and package approaches, best practices, and lessons learned into thought leadership methodologies and published assets; share expertise internally and with customers through workshops, training sessions, and documentation; maintain continuous learning and stay up-to-date with the rapidly evolving GenAI landscape

Requirements

7+ years of experience architecting and delivering enterprise-grade applications with a deep understanding of the full software development lifecycle; 2+ years of experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and integrating LLMs into applications; advanced proficiency in at least one major programming language (e.g., Java, JavaScript, Python, or C#); deep hands-on experience with deployment tooling across Linux, Docker, and Kubernetes environments along with expert-level use of version control systems (e.g., Git, SVN) in enterprise development workflows; demonstrated expertise in deploying and scaling applications across cloud platforms (AWS, Azure, GCP); in-depth knowledge of the generative AI ecosystem including frameworks (e.g., LangChain, LlamaIndex, Haystack) and cloud-native AI platforms (e.g., AWS Bedrock, Google Vertex AI, Azure ML); strong background in data engineering, analytics, or data science with ability to design data pipelines and workflows across structured and unstructured data; deep expertise in graph data modeling and query languages (e.g., Cypher) with practical experience working with graph databases (e.g., Neo4j, Amazon Neptune, TigerGraph) or triple stores (e.g., Ontotext, Stardog); exceptional communication and stakeholder engagement skills with demonstrated ability to influence cross-functional teams; strong analytical mindset with ability to break down complex problems, architect AI solutions, and mentor teams; willingness and ability to travel up to 50% to engage with customers and lead strategic discussions

Benefits

Stock option grant; annual bonus (for certain roles); medical benefits; dental benefits; vision benefits; 401(k); paid time off; certain leaves of absence