Principal AI Solutions Architect

Neo4j

10h • $220,000 - $310,000

About The Position

As a Principal AI Solutions Architect, you will lead the design, construction, and deployment of AI solutions that combine graph databases and AI. You will serve as a trusted advisor to strategic customers, guiding them through complex data challenges and delivering business value. The role calls for expertise in graph technologies, large language models (LLMs), and AI frameworks, and the ability to translate customer needs into production-ready AI applications grounded in real-world context using Neo4j Knowledge Graphs.

You will work with customer leaders and stakeholders to shape Graph+GenAI solutions, design and deploy scalable architectures, and align technical execution with strategic objectives and measurable business outcomes. You will also develop and optimize production-ready AI applications, share expertise through customer and internal education, and contribute field insights and reusable approaches to Neo4j teams and published assets. The role requires willingness and ability to travel up to 50% for customer engagements.

Requirements

• 10+ years of experience architecting and delivering enterprise-grade applications, with deep knowledge of the software development lifecycle and ability to guide complex design and implementation decisions.
• 5+ years of experience working with LLMs, including prompt engineering, fine-tuning, and application integration; current knowledge of LLM providers, their strengths and limitations, and open-source models.
• Advanced proficiency in at least one major programming language, such as Java, JavaScript, Python, or C#, and a track record of delivering clean, maintainable, scalable code in complex systems.
• Hands-on experience with deployment tooling across Linux, Docker, and Kubernetes, and expert-level use of version control systems such as Git or SVN in enterprise development workflows.
• Expertise deploying and scaling applications across AWS, Azure, or GCP, with strategic understanding of cloud-native architecture and DevOps best practices.
• In-depth knowledge of the generative AI ecosystem, including frameworks such as LangChain, LlamaIndex, and Haystack, and familiarity with cloud-native AI platforms such as AWS Bedrock, Google Vertex AI, and Azure ML.
• Strong background in data engineering, analytics, or data science; ability to design pipelines and workflows across structured and unstructured data; hands-on experience with big data technologies such as Hadoop, Spark, or Hive and SQL and NoSQL databases.
• Deep expertise in graph data modeling and query languages such as Cypher, and practical experience with graph databases such as Neo4j, Amazon Neptune, or TigerGraph, or triple stores such as Ontotext or Stardog.
• Exceptional communication and stakeholder engagement skills, including the ability to influence cross-functional teams and align technical decisions with business goals.
• Strong analytical and problem-solving abilities, including the ability to break down complex problems, architect AI solutions, and mentor teams through implementation.
• Willingness and ability to travel up to 50% for customer engagement and project execution.

Responsibilities

• Engage technical leaders, stakeholders, and strategic partners to shape and guide Graph+GenAI implementations, advising decision-makers during complex, high-impact engagements.
• Design and advocate for robust, scalable solution architectures, and lead deployment of Graph+GenAI systems that meet enterprise requirements and industry best practices.
• Understand customer strategic objectives; lead requirements discovery, assess enterprise data ecosystems, and identify opportunities to apply graph-based AI at scale.
• Lead stakeholder engagement to define scope, align priorities, mitigate risks, and support timely delivery while connecting technical execution to business outcomes and measurable impact.
• Develop, test, and deploy production-ready AI applications integrating graph databases, LLMs, and orchestration frameworks; write production-level code and optimize performance, scalability, and integration with customer systems.
• Continuously evaluate and improve deployed AI applications’ performance, scalability, and efficiency, incorporating emerging techniques and technologies.
• Collaborate with Product and Marketing teams to influence the roadmap and share field insights; package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets.
• Share expertise with Neo4j teams and customers through workshops, training, and documentation to help them use, maintain, and reproduce delivered AI solutions.
• Continue learning and stay current with the evolving generative AI landscape, trends, and technologies.
• Travel up to 50% to engage with customers, lead strategic discussions, and support successful project execution.

Benefits

• Medical benefits
• Dental benefits
• Vision benefits
• 401(k)
• Paid time off
• Certain leaves of absence
• Stock option grant
• Annual bonus for certain roles

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed