AI Solutions Architect

Overview

Lead the design, construction, and deployment of AI solutions that combine graph databases and AI, acting as a trusted advisor to strategic customers on complex data challenges.

What you'll do

• Engage technical leaders, stakeholders, and strategic partners to shape and guide the successful implementation of Graph+GenAI solutions, serving as a trusted advisor and thought partner to decision-makers.
• Design and advocate for robust, scalable solution architectures, leading the deployment of Graph+GenAI systems 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 harness the synergy of graph databases and LLMs.
• Lead the discovery of requirements, assess enterprise data ecosystems, and identify opportunities to apply graph-based AI at scale.
• Lead stakeholder engagement across all levels to steer project scope, align on priorities, mitigate risks, and ensure timely delivery, maintaining focus on measurable impact.
• Develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks, including writing production-level code.
• Optimize for performance and scalability and ensure seamless integration with customer systems.
• Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications, incorporating new techniques and technologies as they emerge.
• Work with Product and Marketing teams to influence the roadmap and provide insights from the field, 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.
• Stay up to date with the rapidly evolving GenAI landscape.

What you'll need

• 5+ years of experience architecting and delivering enterprise-grade applications, with a deep understanding of the full software development lifecycle.
• Experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and integrating LLMs into applications.
• Knowledge of different LLM providers and their strengths and limitations, as well as open-source LLMs.
• Advanced proficiency in at least one major programming language (e.g., Java, JavaScript, Python, or C#), with a proven track record of delivering clean, maintainable, and scalable code.
• Deep hands-on experience with deployment tooling across Linux, Docker, and Kubernetes environments.
• 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), with understanding of cloud-native architecture and DevOps best practices.
• In-depth knowledge of the generative AI ecosystem, including frameworks (e.g., LangChain, LlamaIndex, Haystack) and familiarity with cloud-native AI platforms (e.g., AWS Bedrock, Google Vertex AI, Azure ML).
• Strong background in data engineering, analytics, or data science, with the ability to design data pipelines and workflows across structured and unstructured data.
• Hands-on experience with big data technologies (e.g., Hadoop, Spark, Hive) and database systems (SQL and NoSQL).
• 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 a demonstrated ability to influence cross-functional teams and align technical decisions with business goals.
• Strong analytical mindset with the ability to break down complex problems, architect AI solutions, and mentor teams through implementation.
• Willingness and ability to travel up to 50% to engage with customers, lead strategic discussions and ensure successful project execution.

Details

• Location: Remote, United States.
• Annual on-target earnings range: $160,000 to $220,000 USD.
• Eligible for a stock option grant; certain roles are eligible for an annual bonus.
• Travel: up to 50%.