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Salary: USD 200,000 - 265,000 / annual
Neo4j is seeking a Senior AI Solutions Architect to lead the design, construction, and deployment of AI solutions that combine graph databases with generative AI. You will serve as a trusted advisor to strategic enterprise customers, guiding them through complex data challenges and delivering transformative business value.
Key Responsibilities:
Solution Architecting:
- Engage with technical leaders, stakeholders, and strategic partners to shape and guide the implementation of Graph+GenAI solutions, serving as a thought partner to decision-makers in complex, high-impact engagements.
- Design and advocate for robust, scalable solution architectures aligned with complex enterprise requirements and industry best practices.
- Collaborate closely with customer leadership to understand strategic objectives and translate them into high-impact AI solutions that leverage the synergy of graph databases and LLMs.
- Lead stakeholder engagement across all levels to steer project scope, align priorities, mitigate risks, and ensure timely delivery with measurable business impact.
Solution Engineering:
- Develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks, writing production-level code optimized for performance and scalability.
- Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications, incorporating new techniques and technologies as they emerge.
Education & Enablement:
- Work with Neo4j's Product and Marketing teams to influence the roadmap and provide field insights, packaging approaches, best practices, and lessons learned into thought leadership and published assets.
- Share expertise internally and with customers through workshops, training sessions, and documentation to empower them to effectively utilize, maintain, and reproduce delivered AI solutions.
- Maintain continuous learning and stay up-to-date with the rapidly evolving GenAI landscape.
Neo4j is the graph intelligence platform trusted by 84 of the Fortune 100. The company has surpassed $200M in annual recurring revenue, raised over $600M in funding, and is valued at over $2B. You'll work with a world-class team on cutting-edge AI and graph technology.
Requirements:
- Enterprise Application Architecture: 7+ years of experience architecting and delivering enterprise-grade applications, with deep understanding of the full software development lifecycle and ability to guide teams through complex design and implementation decisions.
- LLM Proficiency: 2+ years of experience working with Large Language Models, including prompt engineering, fine-tuning, and integrating LLMs into applications. Knowledge of different LLM providers (commercial and open-source) and their strengths/limitations.
- Programming Proficiency: Advanced proficiency in at least one major programming language (Java, JavaScript, Python, or C#), with proven track record of delivering clean, maintainable, and scalable code within complex systems.
- Deployment and Version Control: Deep hands-on experience with deployment tooling across Linux, Docker, and Kubernetes environments, plus expert-level use of version control systems (Git, SVN) in enterprise development workflows.
- Cloud Computing Expertise: Demonstrated expertise in deploying and scaling applications across cloud platforms (AWS, Azure, GCP), with strategic understanding of cloud-native architecture and DevOps best practices.
- Generative AI Ecosystem Knowledge: In-depth knowledge of the generative AI ecosystem, including frameworks (LangChain, LlamaIndex, Haystack) and cloud-native AI platforms (AWS Bedrock, Google Vertex AI, Azure ML).
- Data & Analytics Fluency: Strong background in data engineering, analytics, or data science, with ability to design data pipelines and workflows across structured and unstructured data. Hands-on experience with big data technologies (Hadoop, Spark, Hive) and database systems (SQL and NoSQL).
- Graph Database Authority: Deep expertise in graph data modeling and query languages (Cypher), with practical experience working with graph databases (Neo4j, Amazon Neptune, TigerGraph) or triple stores (Ontotext, Stardog).
