Senior AI Solutions Architect

Role Description

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.

Key Responsibilities

• Solution Architecting:
  • Engage with technical leaders, stakeholders, and strategic partners to shape and guide the successful implementation of Graph+GenAI solutions.
  • Design and advocate for robust, scalable solution architectures, leading the deployment of Graph+GenAI systems.
  • Collaborate closely with customer leadership to understand their strategic objectives and translate them into high-impact AI solutions.
  • Lead stakeholder engagement across all levels to steer project scope, align on priorities, mitigate risks, and ensure timely delivery.
• Solution Engineering:
  • Develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks.
  • Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications.
• Education & Enablement:
  • Work with other teams at Neo4j to influence the roadmap and provide insights from the field.
  • 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.

Qualifications

• 7+ years of experience architecting and delivering enterprise-grade applications.
• 2+ years of experience working with Large Language Models (LLMs).
• 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.
• Demonstrated expertise in deploying and scaling applications across cloud platforms (AWS, Azure, GCP).
• In-depth knowledge of the generative AI ecosystem and familiarity with cloud-native AI platforms.
• Strong background in data engineering, analytics, or data science.
• Deep expertise in graph data modeling and query languages (e.g., Cypher).
• Exceptional communication and stakeholder engagement skills.
• Strong analytical mindset with the ability to break down complex problems.
• Willingness and ability to travel up to 50% to engage with customers.

Requirements

• Proven track record of delivering clean, maintainable, and scalable code.
• Expert-level use of version control systems (e.g., Git, SVN) in enterprise development workflows.
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Hive) and database systems (SQL and NoSQL).

Benefits

• Stock option grant eligibility.
• Annual bonus eligibility for certain roles.
• Medical, dental, and vision benefits.
• 401(k) plan.
• Paid time off and certain leaves of absence.

Annual On Target Earnings Range

$200,000 — $265,000 USD