Senior AI Solutions Architect

About the role

This position involves designing and building AI solutions that integrate graph databases with advanced AI technologies. You will serve as a key technical advisor to important clients, helping them navigate complex data challenges and achieve significant business outcomes.

Key facts

What you'll do

• Guide strategic customers in implementing Graph+GenAI solutions, acting as a trusted partner in complex projects.
• Develop and champion scalable architectural designs for Graph+GenAI systems that meet enterprise needs and industry standards.
• Collaborate with client leadership to understand strategic goals and translate them into impactful AI applications using graph databases and LLMs.
• Manage stakeholder interactions to define project scope, set priorities, mitigate risks, and ensure timely delivery aligned with business objectives.
• Create, test, and deploy production-ready AI applications that combine graph databases with LLMs and orchestration tools.
• Continuously refine the performance, scalability, and efficiency of deployed AI applications.
• Influence Neo4j's product roadmap and marketing efforts by sharing field insights and best practices.
• Educate customers and internal teams through workshops, training, and documentation.
• Stay current with advancements in generative AI and related technologies.

Requirements

• 7+ years of experience in enterprise application architecture and delivery, with a strong grasp of the software development lifecycle.
• 2+ years of experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and application integration.
• Advanced proficiency in at least one major programming language such as Java, JavaScript, Python, or C#.
• Extensive experience with deployment tools for Linux, Docker, and Kubernetes, and expert-level use of Git.
• Demonstrated expertise in deploying and scaling applications on cloud platforms like AWS, Azure, and GCP.
• Deep understanding of the generative AI landscape, including frameworks like LangChain, LlamaIndex, and Haystack, and cloud AI platforms such as AWS Bedrock, Google Vertex AI, and Azure ML.
• Strong background in data engineering, analytics, or data science, with experience in big data technologies (e.g., Hadoop, Spark) and various database systems (SQL and NoSQL).
• Extensive knowledge of graph data modeling and query languages like Cypher, with practical experience using graph databases such as Neo4j, Amazon Neptune, or TigerGraph.
• Exceptional communication and stakeholder engagement skills.
• Strong analytical and problem-solving abilities.
• Ability to travel up to 50% for customer engagements.

Nice to have

• None specified

Skills & tools

• Graph Databases (Neo4j, Amazon Neptune, TigerGraph)
• LLMs
• Prompt Engineering
• Fine-tuning
• LangChain
• LlamaIndex
• Haystack
• AWS Bedrock
• Google Vertex AI
• Azure ML
• Java
• JavaScript
• Python
• C#
• Linux
• Docker
• Kubernetes
• Git
• AWS
• Azure
• GCP
• Hadoop
• Spark
• Hive
• SQL
• NoSQL
• Cypher

Practical notes

• Annual on target earnings range for this position in the United States is $180,000 - $260,000.
• Travel up to 50% is required.